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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
07340b73d70dfdc6b284b1403d39e1bbdf13bf8f | 1,054 | py | Python | mmdeploy/backend/tensorrt/init_plugins.py | hanrui1sensetime/mmdeploy | f2594c624b67910e55e24418832bd96685425b2f | [
"Apache-2.0"
] | 1 | 2021-12-30T06:29:46.000Z | 2021-12-30T06:29:46.000Z | mmdeploy/backend/tensorrt/init_plugins.py | wwjwy/mmdeploy | c6fccd0121618c8c4dc07f49823c377003475040 | [
"Apache-2.0"
] | null | null | null | mmdeploy/backend/tensorrt/init_plugins.py | wwjwy/mmdeploy | c6fccd0121618c8c4dc07f49823c377003475040 | [
"Apache-2.0"
] | 1 | 2022-02-10T04:31:10.000Z | 2022-02-10T04:31:10.000Z | # Copyright (c) OpenMMLab. All rights reserved.
import ctypes
import glob
import logging
import os
def get_ops_path() -> str:
"""Get path of the TensorRT plugin library.
Returns:
str: A path of the TensorRT plugin library.
"""
wildcard = os.path.abspath(
os.path.join(
os.p... | 26.35 | 77 | 0.642315 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 502 | 0.476281 |
0734297119899a9bd812848f57a6fbe4c63a3822 | 16,800 | py | Python | reagent/test/world_model/test_seq2reward.py | dmitryvinn/ReAgent | f98825b9d021ec353a1f9087840a05fea259bf42 | [
"BSD-3-Clause"
] | null | null | null | reagent/test/world_model/test_seq2reward.py | dmitryvinn/ReAgent | f98825b9d021ec353a1f9087840a05fea259bf42 | [
"BSD-3-Clause"
] | null | null | null | reagent/test/world_model/test_seq2reward.py | dmitryvinn/ReAgent | f98825b9d021ec353a1f9087840a05fea259bf42 | [
"BSD-3-Clause"
] | null | null | null | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
import logging
import os
import random
import unittest
from typing import Optional
import numpy as np
import pytorch_lightning as pl
import torch
import torch.nn as nn
from parameterized import parameterized
from reagent.co... | 35.66879 | 88 | 0.65619 | 7,277 | 0.433155 | 0 | 0 | 1,754 | 0.104405 | 0 | 0 | 1,575 | 0.09375 |
0734fb5dd4a56bdb2ef242b87aea0bcbb002a5dc | 142,160 | py | Python | models_SHOT_convex/syn30m03hfsg.py | grossmann-group/pyomo-MINLP-benchmarking | 714f0a0dffd61675649a805683c0627af6b4929e | [
"MIT"
] | null | null | null | models_SHOT_convex/syn30m03hfsg.py | grossmann-group/pyomo-MINLP-benchmarking | 714f0a0dffd61675649a805683c0627af6b4929e | [
"MIT"
] | null | null | null | models_SHOT_convex/syn30m03hfsg.py | grossmann-group/pyomo-MINLP-benchmarking | 714f0a0dffd61675649a805683c0627af6b4929e | [
"MIT"
] | null | null | null | # MINLP written by GAMS Convert at 01/15/21 11:37:33
#
# Equation counts
# Total E G L N X C B
# 1486 571 111 804 0 0 0 0
#
# Variable counts
# x b i s1s s2s sc ... | 36.090378 | 120 | 0.639913 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 699 | 0.004917 |
07354a91e0ab5c683999d760204ed42f5952201f | 15,695 | py | Python | backend/tests/test_resources.py | sartography/star-drive | c0f33378d42913c3e677e07f74eb46d7b2b82a0a | [
"MIT"
] | null | null | null | backend/tests/test_resources.py | sartography/star-drive | c0f33378d42913c3e677e07f74eb46d7b2b82a0a | [
"MIT"
] | 368 | 2018-12-18T14:43:20.000Z | 2022-03-02T02:54:18.000Z | backend/tests/test_resources.py | sartography/star-drive | c0f33378d42913c3e677e07f74eb46d7b2b82a0a | [
"MIT"
] | 2 | 2019-10-02T03:06:06.000Z | 2020-10-05T16:53:48.000Z | import unittest
from flask import json
from tests.base_test import BaseTest
from app import db, elastic_index
from app.model.resource import Resource
from app.model.resource_category import ResourceCategory
from app.model.resource_change_log import ResourceChangeLog
from app.model.user import Role
class TestResourc... | 47.274096 | 135 | 0.649761 | 15,391 | 0.980631 | 0 | 0 | 0 | 0 | 0 | 0 | 3,217 | 0.20497 |
0735c43eb0b2d2d58ca5e330e9b0ab738257e5f2 | 18,432 | py | Python | kolibri/core/auth/management/commands/sync.py | reubenjacob/kolibri | 028bb2ad63e438c832ff657d37f7b05c3400f2da | [
"MIT"
] | null | null | null | kolibri/core/auth/management/commands/sync.py | reubenjacob/kolibri | 028bb2ad63e438c832ff657d37f7b05c3400f2da | [
"MIT"
] | 8 | 2021-05-21T15:31:24.000Z | 2022-02-24T15:02:14.000Z | kolibri/core/auth/management/commands/sync.py | kuboginichimaru/kolibri | 18b398f62baa1c60f8456f7f9c6d6c9447068f69 | [
"MIT"
] | 1 | 2019-10-05T11:14:40.000Z | 2019-10-05T11:14:40.000Z | import json
import logging
import math
import re
from contextlib import contextmanager
from django.core.management import call_command
from django.core.management.base import CommandError
from morango.models import Filter
from morango.models import InstanceIDModel
from morango.models import ScopeDefinition
from morang... | 34.711864 | 138 | 0.598307 | 16,951 | 0.919651 | 349 | 0.018934 | 887 | 0.048123 | 0 | 0 | 3,990 | 0.216471 |
0735ef32022db6fd8f2cae3cf86a392fe7526086 | 5,787 | py | Python | warp.py | RezaFirouzii/fum-delta-vision | 0a8ad1d434006a9aee0a12c1f021c0bca0bc87e2 | [
"MIT"
] | null | null | null | warp.py | RezaFirouzii/fum-delta-vision | 0a8ad1d434006a9aee0a12c1f021c0bca0bc87e2 | [
"MIT"
] | null | null | null | warp.py | RezaFirouzii/fum-delta-vision | 0a8ad1d434006a9aee0a12c1f021c0bca0bc87e2 | [
"MIT"
] | null | null | null | import math
import imageio
import cv2 as cv
import numpy as np
import transformer
def fix_rotation(img):
img_copy = img.copy()
img = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
rows, cols = img.shape
img = cv.adaptiveThreshold(img, 255, cv.ADAPTIVE_THRESH_MEAN_C, cv.THRESH_BINARY_INV, 15, 9)
kernel = cv.g... | 35.286585 | 122 | 0.556247 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,390 | 0.240194 |
0736759453528b8e50d3977ed9f783e1f7d2c291 | 2,318 | py | Python | sdssobstools/boss_data.py | sdss/ObserverTools | 7f9949341edc91a79dac69d79e24af09e8558ffa | [
"BSD-3-Clause"
] | null | null | null | sdssobstools/boss_data.py | sdss/ObserverTools | 7f9949341edc91a79dac69d79e24af09e8558ffa | [
"BSD-3-Clause"
] | null | null | null | sdssobstools/boss_data.py | sdss/ObserverTools | 7f9949341edc91a79dac69d79e24af09e8558ffa | [
"BSD-3-Clause"
] | null | null | null | #!/usr/bin/env python3
"""
A tool to grab a single BOSS image and pull a few items from its header. It is
used in bin/sloan_log.py, but it could be used directly as well.
"""
import argparse
from pathlib import Path
from astropy.time import Time
import fitsio
class BOSSRaw:
"""A class to parse raw data from APOG... | 34.088235 | 78 | 0.603538 | 1,309 | 0.564711 | 0 | 0 | 0 | 0 | 0 | 0 | 911 | 0.393011 |
0736f9344c10dda2615d756c67d64d15dd48a036 | 955 | py | Python | capitulo-08/ex13b.py | bryan-lima/exercicios-livro-introd-prog-python-3ed | b6bc26dced9728510865704a80cb0d97f81f756b | [
"MIT"
] | 3 | 2021-11-09T17:54:10.000Z | 2022-01-30T22:32:25.000Z | capitulo-08/ex13b.py | bryan-lima/exercicios-livro-introd-prog-python-3ed | b6bc26dced9728510865704a80cb0d97f81f756b | [
"MIT"
] | null | null | null | capitulo-08/ex13b.py | bryan-lima/exercicios-livro-introd-prog-python-3ed | b6bc26dced9728510865704a80cb0d97f81f756b | [
"MIT"
] | null | null | null | # Altere o Programa 8.20 de forma que o usuário tenha três chances de acertar o número
# O programa termina se o usuário acertar ou errar três vezes
# Programa 8.20 do livro, página 184
# Programa 8.20 - Adivinhando o número
#
# import random
#
# n = random.randint(1, 10)
# x = int(input('Escolha um número entre 1 e 1... | 27.285714 | 86 | 0.642932 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 646 | 0.664609 |
0737281036977c90f04b5a6cdebc502ad5e24b6d | 293 | py | Python | slogviz/config.py | mariusfrinken/slogviz | 0557eda336c257245eefe75699eb2479eb672ca1 | [
"MIT"
] | 1 | 2021-05-11T06:54:28.000Z | 2021-05-11T06:54:28.000Z | slogviz/config.py | mariusfrinken/slogviz | 0557eda336c257245eefe75699eb2479eb672ca1 | [
"MIT"
] | null | null | null | slogviz/config.py | mariusfrinken/slogviz | 0557eda336c257245eefe75699eb2479eb672ca1 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""This sub module provides a global variable to check for checking if the non-interactive argument was set
Exported variable:
interactive -- False, if the main the non-interactive argument was set, True, if it was not set
"""
global interactive
interactive = True; | 29.3 | 107 | 0.744027 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 250 | 0.853242 |
0737de527d56f865ee1256abea29660c8dca454e | 894 | py | Python | setup.py | shb84/ATM76 | 433179bde8935abeaf2ace52fe17dedb7a313487 | [
"MIT"
] | null | null | null | setup.py | shb84/ATM76 | 433179bde8935abeaf2ace52fe17dedb7a313487 | [
"MIT"
] | null | null | null | setup.py | shb84/ATM76 | 433179bde8935abeaf2ace52fe17dedb7a313487 | [
"MIT"
] | null | null | null | import setuptools
# To use a consistent encoding
from codecs import open
from os import path
here = path.abspath(path.dirname(__file__))
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
setuptools.setup(
name="atm76",
version="0.1.0",
author="Steven H. Berg... | 27.9375 | 63 | 0.680089 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 328 | 0.36689 |
073976d41a2a2bee70b7facb5e914072923e6d0f | 4,065 | py | Python | agent/check_plugins/download_speed.py | indigos33k3r/god-eye | b2af5ca6dbbd1b302dd5cda1fd0f0c0eee009e76 | [
"BSD-3-Clause"
] | 1 | 2019-04-01T01:59:22.000Z | 2019-04-01T01:59:22.000Z | agent/check_plugins/download_speed.py | indigos33k3r/god-eye | b2af5ca6dbbd1b302dd5cda1fd0f0c0eee009e76 | [
"BSD-3-Clause"
] | null | null | null | agent/check_plugins/download_speed.py | indigos33k3r/god-eye | b2af5ca6dbbd1b302dd5cda1fd0f0c0eee009e76 | [
"BSD-3-Clause"
] | null | null | null | import logging
import asyncio
from agent.check_plugins import AbstractCheckPlugin
# Do khong biet dung thu vien asyncio ntn ca nen em dung thu vien request
# python
import requests
import sys
import time
from datetime import datetime
logger = logging.getLogger(__name__)
class Download(AbstractCheckPlugin):
@as... | 32.007874 | 116 | 0.571218 | 3,799 | 0.931356 | 871 | 0.213533 | 1,868 | 0.457955 | 0 | 0 | 1,668 | 0.408924 |
073a8f2eb2cea5666b00d9e848e53968468e9ca6 | 130 | py | Python | Setup Rich Text Editor/mysite/main/urls.py | AyemunHossain/Django | 0b1ed21fd6bd2906a4a1a220c029a2193658320f | [
"MIT"
] | 2 | 2020-02-14T19:23:50.000Z | 2020-04-19T08:26:38.000Z | Setup Rich Text Editor/mysite/main/urls.py | AyemunHossain/Django | 0b1ed21fd6bd2906a4a1a220c029a2193658320f | [
"MIT"
] | 42 | 2021-02-02T23:08:30.000Z | 2022-03-12T00:54:55.000Z | Setup Rich Text Editor/mysite/main/urls.py | AyemunHossain/Django | 0b1ed21fd6bd2906a4a1a220c029a2193658320f | [
"MIT"
] | 1 | 2022-03-07T08:09:41.000Z | 2022-03-07T08:09:41.000Z | from django.urls import path
from . import views
app_name = "main"
urlpatterns = [
path("",views.homepage,name="homepage")
] | 16.25 | 43 | 0.7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 18 | 0.138462 |
073aa245c28c69910b8c705ef18f357b5c9e4c5f | 5,846 | py | Python | GA/train.py | jcordell/keras-optimization | cbda84bcf3b31928d829af4afc82af1886877341 | [
"MIT"
] | 1 | 2017-05-29T13:48:22.000Z | 2017-05-29T13:48:22.000Z | GA/train.py | jcordell/keras-optimization | cbda84bcf3b31928d829af4afc82af1886877341 | [
"MIT"
] | null | null | null | GA/train.py | jcordell/keras-optimization | cbda84bcf3b31928d829af4afc82af1886877341 | [
"MIT"
] | null | null | null | """
Utility used by the Network class to actually train.
Based on:
https://github.com/fchollet/keras/blob/master/examples/mnist_mlp.py
"""
from keras.datasets import mnist, cifar10
from keras.models import Sequential
from keras.layers import Dense, Dropout
from keras.utils.np_utils import to_categorical
from kera... | 33.028249 | 113 | 0.653609 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,556 | 0.266165 |
073abd8b8de49a73d08e10cf329cea3aaaac91fa | 491 | py | Python | tests/integration/agenda/test_models.py | rolandgeider/OpenSlides | 331141c17cb23da26e377d4285efdb4a50753a59 | [
"MIT"
] | null | null | null | tests/integration/agenda/test_models.py | rolandgeider/OpenSlides | 331141c17cb23da26e377d4285efdb4a50753a59 | [
"MIT"
] | null | null | null | tests/integration/agenda/test_models.py | rolandgeider/OpenSlides | 331141c17cb23da26e377d4285efdb4a50753a59 | [
"MIT"
] | null | null | null | from openslides.agenda.models import Item
from openslides.core.models import CustomSlide
from openslides.utils.test import TestCase
class TestItemManager(TestCase):
def test_get_root_and_children_db_queries(self):
"""
Test that get_root_and_children needs only one db query.
"""
for... | 30.6875 | 64 | 0.700611 | 356 | 0.725051 | 0 | 0 | 0 | 0 | 0 | 0 | 88 | 0.179226 |
073cf557d5c1841920fb8cd559522daa79d5440d | 3,272 | py | Python | ssl_context_builder/http_impl/requests_wrapper/secure_session.py | mbjahnoon/ssl_context_builder | e73530f900b56710c705675e8e657f0bd17f7c07 | [
"Apache-2.0"
] | 1 | 2022-03-01T16:27:33.000Z | 2022-03-01T16:27:33.000Z | ssl_context_builder/http_impl/requests_wrapper/secure_session.py | mbjahnoon/ssl_context_builder | e73530f900b56710c705675e8e657f0bd17f7c07 | [
"Apache-2.0"
] | null | null | null | ssl_context_builder/http_impl/requests_wrapper/secure_session.py | mbjahnoon/ssl_context_builder | e73530f900b56710c705675e8e657f0bd17f7c07 | [
"Apache-2.0"
] | null | null | null | import weakref
import os
import requests
import ssl
from ssl import SSLContext
import logging
from ssl_context_builder.builder.builder import SslContextBuilder
from ssl_context_builder.http_impl.requests_wrapper.ssl_adapter import SslAdapter
class RequestsSecureSession:
def __init__(self, ssl_context: SSLContex... | 34.808511 | 120 | 0.637531 | 3,026 | 0.924817 | 0 | 0 | 1,475 | 0.450795 | 0 | 0 | 1,157 | 0.353606 |
073ddb35cfd257b4fe7bee31f410bb17b18b0611 | 621 | py | Python | tiny_scripts/select_cifar_10.py | jiaqiangwjq/python_workhouse | c0e739d8bc8ea3d318a0f916e9d79b1f4d4acad9 | [
"Unlicense"
] | null | null | null | tiny_scripts/select_cifar_10.py | jiaqiangwjq/python_workhouse | c0e739d8bc8ea3d318a0f916e9d79b1f4d4acad9 | [
"Unlicense"
] | null | null | null | tiny_scripts/select_cifar_10.py | jiaqiangwjq/python_workhouse | c0e739d8bc8ea3d318a0f916e9d79b1f4d4acad9 | [
"Unlicense"
] | null | null | null | '''
Selected cifar-10. The .csv file format:
class_index,data_index
3,0
8,1
8,2
...
'''
import pickle
import pandas as pd
file = 'E:\pycharm\LEARN\data\cifar-10\cifar-10-batches-py\\test_batch'
with open(file, 'rb') as f:
dict = pickle.load(f, encoding='bytes')
dict.keys()
batch_label = dict[b'batch_label']
... | 18.818182 | 71 | 0.710145 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 253 | 0.407407 |
074082800249cdc23669711e86fb83230db924ee | 940 | py | Python | codebox/scripts/fixture.py | disqus/codebox | 9f8e1a9c08c6a79bf3519782be483ff9763c4b4e | [
"Apache-2.0"
] | 5 | 2015-09-24T19:53:02.000Z | 2019-05-14T11:56:07.000Z | codebox/scripts/fixture.py | disqus/codebox | 9f8e1a9c08c6a79bf3519782be483ff9763c4b4e | [
"Apache-2.0"
] | null | null | null | codebox/scripts/fixture.py | disqus/codebox | 9f8e1a9c08c6a79bf3519782be483ff9763c4b4e | [
"Apache-2.0"
] | null | null | null | # Ghetto Fixtures
from codebox import app
from codebox.apps.auth.models import User
from codebox.apps.snippets.models import Snippet
from codebox.apps.organizations.models import Organization, OrganizationMember
from flask import g
client = app.test_client()
_ctx = app.test_request_context()
_ctx.push()
app.preproces... | 29.375 | 99 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 263 | 0.279787 |
0740a865caa54dd6749985e9ca6d8ad7824f4098 | 3,062 | py | Python | corehq/apps/linked_domain/tests/test_views.py | akashkj/commcare-hq | b00a62336ec26cea1477dfb8c048c548cc462831 | [
"BSD-3-Clause"
] | null | null | null | corehq/apps/linked_domain/tests/test_views.py | akashkj/commcare-hq | b00a62336ec26cea1477dfb8c048c548cc462831 | [
"BSD-3-Clause"
] | null | null | null | corehq/apps/linked_domain/tests/test_views.py | akashkj/commcare-hq | b00a62336ec26cea1477dfb8c048c548cc462831 | [
"BSD-3-Clause"
] | null | null | null | from unittest.mock import Mock, patch
from django.test import SimpleTestCase
from corehq.apps.domain.exceptions import DomainDoesNotExist
from corehq.apps.linked_domain.exceptions import (
DomainLinkAlreadyExists,
DomainLinkError,
DomainLinkNotAllowed,
)
from corehq.apps.linked_domain.views import link_do... | 48.603175 | 112 | 0.736447 | 2,733 | 0.892554 | 0 | 0 | 173 | 0.056499 | 0 | 0 | 735 | 0.240039 |
0740aa099c767617a2ec263fb4853c2833c7342f | 79 | py | Python | LanguageBasics/functions/import_eg.py | Vamsi-TM/jubilant-train | a3ca0216e161ead4f59d923a36587098790beb5d | [
"MIT"
] | null | null | null | LanguageBasics/functions/import_eg.py | Vamsi-TM/jubilant-train | a3ca0216e161ead4f59d923a36587098790beb5d | [
"MIT"
] | null | null | null | LanguageBasics/functions/import_eg.py | Vamsi-TM/jubilant-train | a3ca0216e161ead4f59d923a36587098790beb5d | [
"MIT"
] | null | null | null | import function_exercise_01 as st
st.sandwich_toppings('meatballs', 'salad')
| 15.8 | 42 | 0.797468 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 18 | 0.227848 |
0740e77524f70aef71e87bb08ca6fba979752644 | 2,207 | py | Python | pyingest/parsers/zenodo.py | golnazads/adsabs-pyingest | 37b37dd9e0d8a6e5cc34c59d30acd14e3381b48e | [
"MIT"
] | 1 | 2020-06-04T20:09:03.000Z | 2020-06-04T20:09:03.000Z | pyingest/parsers/zenodo.py | golnazads/adsabs-pyingest | 37b37dd9e0d8a6e5cc34c59d30acd14e3381b48e | [
"MIT"
] | 81 | 2017-11-16T16:07:21.000Z | 2022-03-08T14:05:37.000Z | pyingest/parsers/zenodo.py | golnazads/adsabs-pyingest | 37b37dd9e0d8a6e5cc34c59d30acd14e3381b48e | [
"MIT"
] | 17 | 2016-04-13T17:03:25.000Z | 2021-12-22T15:26:54.000Z | #!/usr/bin/python
#
#
from __future__ import absolute_import
import json
import re
import logging
from .datacite import DataCiteParser
class WrongPublisherException(Exception):
pass
class ZenodoParser(DataCiteParser):
def get_references(self, r):
# as of version 3.1 of datacite schema, "References... | 30.232877 | 101 | 0.566833 | 1,645 | 0.745356 | 0 | 0 | 0 | 0 | 0 | 0 | 1,009 | 0.457182 |
07421cfb41d4ae2f25674d5123c3192c8a85313e | 25,223 | py | Python | src/fullnode.py | AmeyaDaddikar/vjtichain | 2a9b68d475fe5cc2babdf3f5b463a685e8423f05 | [
"MIT"
] | 1 | 2019-05-26T12:36:37.000Z | 2019-05-26T12:36:37.000Z | src/fullnode.py | AmeyaDaddikar/vjtichain | 2a9b68d475fe5cc2babdf3f5b463a685e8423f05 | [
"MIT"
] | null | null | null | src/fullnode.py | AmeyaDaddikar/vjtichain | 2a9b68d475fe5cc2babdf3f5b463a685e8423f05 | [
"MIT"
] | null | null | null | import json
import time
from functools import lru_cache
from multiprocessing import Pool, Process
from threading import Thread, Timer
from typing import Any, Dict, List
from datetime import datetime
import hashlib
import inspect
import requests
import waitress
from bottle import BaseTemplate, Bottle, request, response,... | 34.223881 | 203 | 0.632082 | 0 | 0 | 0 | 0 | 12,914 | 0.511993 | 0 | 0 | 7,045 | 0.279309 |
074273af8a268ef926e75f5dce65175c9bfb7048 | 5,914 | py | Python | deepexplain/tf/v1_x/main.py | alexus37/MasterThesisCode | a7eada603686de75968acc8586fd307a91b0491b | [
"MIT"
] | 1 | 2020-04-23T15:39:27.000Z | 2020-04-23T15:39:27.000Z | deepexplain/tf/v1_x/main.py | alexus37/DeepExplain | a7eada603686de75968acc8586fd307a91b0491b | [
"MIT"
] | null | null | null | deepexplain/tf/v1_x/main.py | alexus37/DeepExplain | a7eada603686de75968acc8586fd307a91b0491b | [
"MIT"
] | null | null | null | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
from tensorflow.python.framework import ops
from collections import OrderedDict
import warnings, logging
from deepexplain.tf.v1_x import constants
from deepexplain.tf.v1_x.baseClasses i... | 46.566929 | 153 | 0.672979 | 4,472 | 0.756172 | 0 | 0 | 573 | 0.096889 | 0 | 0 | 1,525 | 0.257863 |
074414b6699fea23b4050feee569e12a24d49670 | 1,457 | py | Python | util/mem_usage.py | robinupham/cnn_lensing | f5d4defc7e2c5b7a23744051da904526d04c27c8 | [
"MIT"
] | null | null | null | util/mem_usage.py | robinupham/cnn_lensing | f5d4defc7e2c5b7a23744051da904526d04c27c8 | [
"MIT"
] | null | null | null | util/mem_usage.py | robinupham/cnn_lensing | f5d4defc7e2c5b7a23744051da904526d04c27c8 | [
"MIT"
] | null | null | null | """
Get the memory usage of a Keras model.
From https://stackoverflow.com/a/46216013.
"""
def get_model_memory_usage(batch_size, model):
"""
Get the memory usage of a Keras model in GB.
From https://stackoverflow.com/a/46216013.
"""
import numpy as np
try:
from keras import backend a... | 30.354167 | 104 | 0.649279 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 223 | 0.153054 |
0744b878366a1f07bc8ae64bebfadf9106c8ad3a | 303 | py | Python | hexrd/distortion/distortionabc.py | glemaitre/hexrd | b68b1ba72e0f480d29bdaae2adbd6c6e2380cc7c | [
"BSD-3-Clause"
] | 27 | 2020-02-18T12:15:08.000Z | 2022-03-24T17:53:46.000Z | hexrd/distortion/distortionabc.py | glemaitre/hexrd | b68b1ba72e0f480d29bdaae2adbd6c6e2380cc7c | [
"BSD-3-Clause"
] | 259 | 2020-02-02T22:18:29.000Z | 2022-03-30T19:59:58.000Z | hexrd/distortion/distortionabc.py | glemaitre/hexrd | b68b1ba72e0f480d29bdaae2adbd6c6e2380cc7c | [
"BSD-3-Clause"
] | 11 | 2020-02-18T12:14:44.000Z | 2022-03-04T16:19:11.000Z | import abc
class DistortionABC(metaclass=abc.ABCMeta):
maptype = None
@abc.abstractmethod
def apply(self, xy_in):
"""Apply distortion mapping"""
pass
@abc.abstractmethod
def apply_inverse(self, xy_in):
"""Apply inverse distortion mapping"""
pass
| 17.823529 | 46 | 0.633663 | 289 | 0.953795 | 0 | 0 | 214 | 0.706271 | 0 | 0 | 68 | 0.224422 |
0745c582ad840fd55885e6625d498a1f4e1e1d0a | 799 | py | Python | setup.py | statisticianinstilettos/recommender_metrics | 82091ec53eb8b3527f95755006237658deb03c18 | [
"MIT"
] | null | null | null | setup.py | statisticianinstilettos/recommender_metrics | 82091ec53eb8b3527f95755006237658deb03c18 | [
"MIT"
] | null | null | null | setup.py | statisticianinstilettos/recommender_metrics | 82091ec53eb8b3527f95755006237658deb03c18 | [
"MIT"
] | null | null | null | import io
import os
from setuptools import setup
def read(file_name):
"""Read a text file and return the content as a string."""
with io.open(os.path.join(os.path.dirname(__file__), file_name),
encoding='utf-8') as f:
return f.read()
setup(
name='recmetrics',
url='https://gi... | 25.774194 | 73 | 0.644556 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 328 | 0.410513 |
0745f258c3fda6d1caa28babca894afcfee11f9f | 10,829 | py | Python | run_classifier.py | wj-Mcat/model-getting-started | abe8c9df10b45841eeb38e859e680a37ec03fe8a | [
"Apache-2.0"
] | null | null | null | run_classifier.py | wj-Mcat/model-getting-started | abe8c9df10b45841eeb38e859e680a37ec03fe8a | [
"Apache-2.0"
] | null | null | null | run_classifier.py | wj-Mcat/model-getting-started | abe8c9df10b45841eeb38e859e680a37ec03fe8a | [
"Apache-2.0"
] | null | null | null | # coding=utf-8
# Copyright 2018 The Google AI Language Team 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 ... | 38.537367 | 122 | 0.651676 | 211 | 0.019388 | 0 | 0 | 0 | 0 | 0 | 0 | 2,705 | 0.248553 |
07461f1a486f88f500aad5210c29f31d3c93dac1 | 1,174 | py | Python | module2-sql-for-analysis/rpg_db.py | TobyChen320/DS-Unit-3-Sprint-2-SQL-and-Databases | 306d2252b3756a501e2412fcb5eddbdebc16a362 | [
"MIT"
] | null | null | null | module2-sql-for-analysis/rpg_db.py | TobyChen320/DS-Unit-3-Sprint-2-SQL-and-Databases | 306d2252b3756a501e2412fcb5eddbdebc16a362 | [
"MIT"
] | null | null | null | module2-sql-for-analysis/rpg_db.py | TobyChen320/DS-Unit-3-Sprint-2-SQL-and-Databases | 306d2252b3756a501e2412fcb5eddbdebc16a362 | [
"MIT"
] | null | null | null | import sqlite3
import os
import psycopg2
from dotenv import load_dotenv
load_dotenv()
DB_NAME2 = os.getenv("DB_NAME3")
DB_USER2 = os.getenv("DB_USER3")
DB_PASS2 = os.getenv("DB_PASS3")
DB_HOST2 = os.getenv("DB_HOST3")
conn = psycopg2.connect(dbname=DB_NAME2,
user=DB_USER2,
... | 22.150943 | 94 | 0.698467 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 465 | 0.396082 |
0748c347781432c41ed5dc21b2a78b229eb50e78 | 24,232 | py | Python | sws_comp_wiki_gen.py | moff-wildfire/sws-battlefy | 04b12b54f91e450980c2c57eed57f0504abec1bb | [
"Unlicense"
] | 1 | 2021-12-10T01:36:36.000Z | 2021-12-10T01:36:36.000Z | sws_comp_wiki_gen.py | moff-wildfire/sws-battlefy | 04b12b54f91e450980c2c57eed57f0504abec1bb | [
"Unlicense"
] | null | null | null | sws_comp_wiki_gen.py | moff-wildfire/sws-battlefy | 04b12b54f91e450980c2c57eed57f0504abec1bb | [
"Unlicense"
] | null | null | null | import battlefy_data
import battlefy_wiki_linkings
from datetime import datetime
from operator import itemgetter
from pathlib import Path
import calcup_roster_tracking
def create_sidebar(data, wiki_name):
sidebar = '{{Infobox league' + '\n'
sidebar += '|liquipediatier=' + '\n'
sidebar += '|name=' + data[... | 42.812721 | 119 | 0.560333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8,219 | 0.33918 |
0748f0d589516cda25a4a57eb049a757da513fda | 3,169 | py | Python | utilidades/texto.py | DeadZombie14/chillMagicCarPygame | 756bb6d27939bed3c2834222d03096e90f05a788 | [
"MIT"
] | null | null | null | utilidades/texto.py | DeadZombie14/chillMagicCarPygame | 756bb6d27939bed3c2834222d03096e90f05a788 | [
"MIT"
] | null | null | null | utilidades/texto.py | DeadZombie14/chillMagicCarPygame | 756bb6d27939bed3c2834222d03096e90f05a788 | [
"MIT"
] | null | null | null | import pygame
class Texto:
def __init__(self, screen, text, x, y, text_size = 20, fuente = 'Calibri', italic = False, bold= False, subrayado= False, color = (250, 240, 230), bg = [] ):
self.screen = screen
fg = color
self.coord = x, y
#load font, prepare values
f... | 31.376238 | 161 | 0.517829 | 2,905 | 0.916693 | 0 | 0 | 0 | 0 | 0 | 0 | 840 | 0.265068 |
074906b7cce1eac2c3d5b9dbf7a25ead70cb372d | 11,662 | py | Python | training_xgboost_model.py | MighTy-Weaver/Inefficient-AC-detection | 8229f19accd1569ba7b48f77f71783173393d9ed | [
"Apache-2.0"
] | 2 | 2021-02-21T13:28:30.000Z | 2021-07-10T05:24:05.000Z | training_xgboost_model.py | MighTy-Weaver/Inefficient-AC-detection | 8229f19accd1569ba7b48f77f71783173393d9ed | [
"Apache-2.0"
] | null | null | null | training_xgboost_model.py | MighTy-Weaver/Inefficient-AC-detection | 8229f19accd1569ba7b48f77f71783173393d9ed | [
"Apache-2.0"
] | null | null | null | # This is the code to train the xgboost model with cross-validation for each unique room in the dataset.
# Models are dumped into ./models and results are dumped into two csv files in the current work directory.
import argparse
import json
import math
import os
import pickle
import warnings
from typing import Tuple
i... | 51.149123 | 120 | 0.667038 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3,956 | 0.339221 |
07494bf06325a1ec59e4ef3f00ab6c72a53bc972 | 1,293 | py | Python | setup.py | editorconfig/editorconfig-core-py | f43312abcf6888b78ca80f1e95bfa627281746ad | [
"PSF-2.0",
"BSD-2-Clause"
] | 70 | 2015-01-12T09:55:18.000Z | 2022-03-29T06:15:49.000Z | setup.py | editorconfig/editorconfig-core-py | f43312abcf6888b78ca80f1e95bfa627281746ad | [
"PSF-2.0",
"BSD-2-Clause"
] | 26 | 2015-09-15T06:46:51.000Z | 2022-03-28T08:56:35.000Z | setup.py | editorconfig/editorconfig-core-py | f43312abcf6888b78ca80f1e95bfa627281746ad | [
"PSF-2.0",
"BSD-2-Clause"
] | 28 | 2015-04-05T18:07:16.000Z | 2022-03-28T08:08:00.000Z | import os
from setuptools import setup
# Read the version
g = {}
with open(os.path.join("editorconfig", "version.py"), "rt") as fp:
exec(fp.read(), g)
v = g['VERSION']
version = ".".join(str(x) for x in v[:3])
if v[3] != "final":
version += "-" + v[3]
setup(
name='EditorConfig',
versio... | 31.536585 | 72 | 0.590101 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 737 | 0.569992 |
074981b228683f09166c88b994c571524093496b | 6,035 | py | Python | multi_group_memory_contrast.py | wangzy0327/hadoop-cluster-docker | cf1de6bf458ade132ad5a688e4f8f9b9968a704a | [
"Apache-2.0"
] | 1 | 2020-03-03T10:16:33.000Z | 2020-03-03T10:16:33.000Z | multi_group_memory_contrast.py | wangzy0327/hadoop-cluster-docker | cf1de6bf458ade132ad5a688e4f8f9b9968a704a | [
"Apache-2.0"
] | null | null | null | multi_group_memory_contrast.py | wangzy0327/hadoop-cluster-docker | cf1de6bf458ade132ad5a688e4f8f9b9968a704a | [
"Apache-2.0"
] | 1 | 2020-12-21T09:20:52.000Z | 2020-12-21T09:20:52.000Z | import numpy as np
import matplotlib.pyplot as plt
t = np.arange(0,375,6.5)
# MEM_1 = [0.031, 0.034, 0.034, 0.034, 0.031, 0.034, 0.034, 0.034, 0.031, 0.033, 0.035, 0.034, 0.031, 0.033, 0.034, 0.034, 0.031, 0.033, 0.034, 0.034, 0.031, 0.033, 0.034, 0.034, 0.031, 0.033, 0.034, 0.034, 0.031, 0.031, 0.031, 0.031, 0.031, 0... | 104.051724 | 414 | 0.596189 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2,432 | 0.402983 |
0749f9a616656fe35e1c0d2532a8c8a5e40dc4ab | 1,042 | py | Python | vaping/config.py | josephburnett/vaping | 16f9092f0b3c1692e6d1a040f746e1277e197353 | [
"Apache-2.0"
] | null | null | null | vaping/config.py | josephburnett/vaping | 16f9092f0b3c1692e6d1a040f746e1277e197353 | [
"Apache-2.0"
] | null | null | null | vaping/config.py | josephburnett/vaping | 16f9092f0b3c1692e6d1a040f746e1277e197353 | [
"Apache-2.0"
] | null | null | null | import re
import munge
def parse_interval(val):
"""
converts a string to float of seconds
.5 = 500ms
90 = 1m30s
**Arguments**
- val (`str`)
"""
re_intv = re.compile(r"([\d\.]+)([a-zA-Z]+)")
val = val.strip()
total = 0.0
for match in re_intv.findall(val):
... | 20.84 | 86 | 0.46833 | 271 | 0.260077 | 0 | 0 | 0 | 0 | 0 | 0 | 341 | 0.327255 |
074b42be48178517185311cda7a91881826a6fd2 | 654 | py | Python | sktime/annotation/tests/test_all_annotators.py | Rubiel1/sktime | 2fd2290fb438224f11ddf202148917eaf9b73a87 | [
"BSD-3-Clause"
] | 1 | 2021-09-08T14:24:52.000Z | 2021-09-08T14:24:52.000Z | sktime/annotation/tests/test_all_annotators.py | Rubiel1/sktime | 2fd2290fb438224f11ddf202148917eaf9b73a87 | [
"BSD-3-Clause"
] | null | null | null | sktime/annotation/tests/test_all_annotators.py | Rubiel1/sktime | 2fd2290fb438224f11ddf202148917eaf9b73a87 | [
"BSD-3-Clause"
] | null | null | null | # -*- coding: utf-8 -*-
"""Tests for sktime annotators."""
import pandas as pd
import pytest
from sktime.registry import all_estimators
from sktime.utils._testing.estimator_checks import _make_args
ALL_ANNOTATORS = all_estimators(estimator_types="series-annotator", return_names=False)
@pytest.mark.parametrize("Est... | 28.434783 | 87 | 0.750765 | 0 | 0 | 0 | 0 | 362 | 0.553517 | 0 | 0 | 133 | 0.203364 |
074b7ef708bdd483e5b790825c69a90db600e852 | 569 | py | Python | raspberry-pi-camera/cam.py | AlexMassin/mlh-react-vr-website | dc08788ccdecc9923b8dbfd31fa452cb83d214ae | [
"MIT"
] | 1 | 2019-05-19T03:37:26.000Z | 2019-05-19T03:37:26.000Z | raspberry-pi-camera/cam.py | AlexMassin/mlh-react-vr-website | dc08788ccdecc9923b8dbfd31fa452cb83d214ae | [
"MIT"
] | null | null | null | raspberry-pi-camera/cam.py | AlexMassin/mlh-react-vr-website | dc08788ccdecc9923b8dbfd31fa452cb83d214ae | [
"MIT"
] | 1 | 2019-10-02T20:18:54.000Z | 2019-10-02T20:18:54.000Z | picamera import PiCamera
from time import sleep
import boto3
import os.path
import subprocess
s3 = boto3.client('s3')
bucket = 'cambucket21'
camera = PiCamera()
#camera.resolution(1920,1080)
x = 0
camerafile = x
while True:
if (x == 6):
x = 1
else:
x = x + 1
camera.start_preview()
camera.start_recording('/home/pi/' ... | 20.321429 | 82 | 0.671353 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 126 | 0.221441 |
074b9d7491ffbc8fda4dfce94456f63c57933830 | 437 | py | Python | Part_3_advanced/m04_datetime_and_timedelta/datetime_formats/example_1.py | Mikma03/InfoShareacademy_Python_Courses | 3df1008c8c92831bebf1625f960f25b39d6987e6 | [
"MIT"
] | null | null | null | Part_3_advanced/m04_datetime_and_timedelta/datetime_formats/example_1.py | Mikma03/InfoShareacademy_Python_Courses | 3df1008c8c92831bebf1625f960f25b39d6987e6 | [
"MIT"
] | null | null | null | Part_3_advanced/m04_datetime_and_timedelta/datetime_formats/example_1.py | Mikma03/InfoShareacademy_Python_Courses | 3df1008c8c92831bebf1625f960f25b39d6987e6 | [
"MIT"
] | null | null | null | from datetime import datetime
def run_example():
moment_in_time = datetime.fromordinal(256)
print(moment_in_time)
print(moment_in_time.toordinal())
print(moment_in_time.weekday())
print(moment_in_time.isoweekday())
other_moment = datetime.fromtimestamp(16_000_000)
print(other_moment)
... | 23 | 53 | 0.734554 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 0.022883 |
074c422d6b8b108e68ca3caffc0062b15b80774b | 1,333 | py | Python | examples/scripts/segmentation/nnet3-segmenter.py | mxmpl/pykaldi | 0570307138c5391cc47b019450d08bcb9686dd98 | [
"Apache-2.0"
] | 916 | 2017-11-22T19:33:36.000Z | 2022-03-31T11:51:58.000Z | examples/scripts/segmentation/nnet3-segmenter.py | mxmpl/pykaldi | 0570307138c5391cc47b019450d08bcb9686dd98 | [
"Apache-2.0"
] | 268 | 2018-01-16T22:06:45.000Z | 2022-03-29T03:24:41.000Z | examples/scripts/segmentation/nnet3-segmenter.py | mxmpl/pykaldi | 0570307138c5391cc47b019450d08bcb9686dd98 | [
"Apache-2.0"
] | 260 | 2018-01-23T18:39:40.000Z | 2022-03-24T08:17:39.000Z | #!/usr/bin/env python
from __future__ import print_function
from kaldi.segmentation import NnetSAD, SegmentationProcessor
from kaldi.nnet3 import NnetSimpleComputationOptions
from kaldi.util.table import SequentialMatrixReader
# Construct SAD
model = NnetSAD.read_model("final.raw")
post = NnetSAD.read_average_poster... | 37.027778 | 77 | 0.775694 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 241 | 0.180795 |
074c987bce7bacca56810d03a725dd7cdf352776 | 4,911 | py | Python | src/dataset.py | HeegyuKim/CurseFilter | dc4a64aebd997706553c24e919a88e19a3c92dd3 | [
"MIT"
] | null | null | null | src/dataset.py | HeegyuKim/CurseFilter | dc4a64aebd997706553c24e919a88e19a3c92dd3 | [
"MIT"
] | null | null | null | src/dataset.py | HeegyuKim/CurseFilter | dc4a64aebd997706553c24e919a88e19a3c92dd3 | [
"MIT"
] | null | null | null | from cProfile import label
from matplotlib.pyplot import text
import pandas as pd
import numpy as np
from tokenizers import Tokenizer
import torch
from torch.utils.data import Dataset, DataLoader
from typing import Dict, Any, Tuple
from datasets import load_dataset
class DataFrameDataset(Dataset):
def __init__(se... | 38.069767 | 131 | 0.609448 | 4,632 | 0.943189 | 0 | 0 | 0 | 0 | 0 | 0 | 153 | 0.031155 |
074cdaf58b71e5a0a7b4da96e1a1535d7fb91e4b | 987 | py | Python | helper_tools/raspi_OMX-Player_Howto_demo.py | stko/Schnipsl | 824572c657e48f18950f584b9529661ff5bb8069 | [
"MIT"
] | null | null | null | helper_tools/raspi_OMX-Player_Howto_demo.py | stko/Schnipsl | 824572c657e48f18950f584b9529661ff5bb8069 | [
"MIT"
] | 29 | 2020-08-30T15:07:50.000Z | 2022-02-19T03:41:26.000Z | helper_tools/raspi_OMX-Player_Howto_demo.py | wifitvbox/Schnipsl | 553ce8de3dda26fb92297ad76e92f4a363070e4e | [
"MIT"
] | 1 | 2020-12-28T05:46:17.000Z | 2020-12-28T05:46:17.000Z | #!/usr/bin/python
# mp4museum.org by julius schmiedel 2019
import os
import sys
import glob
from subprocess import Popen, PIPE
import RPi.GPIO as GPIO
FNULL = open(os.devnull, "w")
# setup GPIO pin
GPIO.setmode(GPIO.BOARD)
GPIO.setup(11, GPIO.IN, pull_up_down = GPIO.PUD_DOWN)
GPIO.setup(13, GPIO.IN, pull_up_down = ... | 25.973684 | 97 | 0.73151 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 282 | 0.285714 |
074ce069ee533cbcb1f8fc2b612416adfbbf158a | 4,549 | py | Python | dash_app/compare_alg.py | zeyu2001/ICT1002-Python | 76a2c8ad3e3c4a3c873a9259e2a11488c33f2bf7 | [
"MIT"
] | 1 | 2020-10-31T06:57:01.000Z | 2020-10-31T06:57:01.000Z | dash_app/compare_alg.py | zeyu2001/ICT1002-Python | 76a2c8ad3e3c4a3c873a9259e2a11488c33f2bf7 | [
"MIT"
] | null | null | null | dash_app/compare_alg.py | zeyu2001/ICT1002-Python | 76a2c8ad3e3c4a3c873a9259e2a11488c33f2bf7 | [
"MIT"
] | 1 | 2021-12-04T10:02:16.000Z | 2021-12-04T10:02:16.000Z | """
Comparison between the efficiency of the Boyer-Moore algorithm and the naive substring search algorithm.
The runtimes for both algorithms are plotted on the same axes.
"""
import matplotlib.pyplot as plt
import numpy as np
import string
import time
import random
from bm_alg import boyer_moore_match, naive_match
#... | 28.254658 | 104 | 0.585843 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,485 | 0.326445 |
074fa8cb751dc3e01a0d7cf156f12acfd22b5c7b | 616 | py | Python | TSIS_3/3774.py | GMKanat/PP2_spring | 423617d559c5690f689741aaa152b9fee5082baf | [
"MIT"
] | null | null | null | TSIS_3/3774.py | GMKanat/PP2_spring | 423617d559c5690f689741aaa152b9fee5082baf | [
"MIT"
] | null | null | null | TSIS_3/3774.py | GMKanat/PP2_spring | 423617d559c5690f689741aaa152b9fee5082baf | [
"MIT"
] | null | null | null | ans = dict()
pairs = dict()
def create_tree(p):
if p in ans:
return ans[p]
else:
try:
res = 0
if p in pairs:
for ch in pairs[p]:
res += create_tree(ch) + 1
ans[p] = res
return res
except:
pass... | 22.814815 | 46 | 0.469156 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
075329f4475d143e6e7eeffda251a30feb1872ce | 404 | py | Python | italicizer.py | Dorijan-Cirkveni/Miniprojects | 2109275c9c1b9f5e7a286604cbb1b7966dff9798 | [
"MIT"
] | null | null | null | italicizer.py | Dorijan-Cirkveni/Miniprojects | 2109275c9c1b9f5e7a286604cbb1b7966dff9798 | [
"MIT"
] | null | null | null | italicizer.py | Dorijan-Cirkveni/Miniprojects | 2109275c9c1b9f5e7a286604cbb1b7966dff9798 | [
"MIT"
] | null | null | null | def italicize(s):
b = False
res = ''
for e in s:
if e == '"':
if b:
res += '{\\i}' + e
else:
res += e + '{i}'
b=not b
else:
res += e
return res
def main():
F=open('test_in.txt','r')
X=F.read()
F... | 15.538462 | 34 | 0.368812 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 43 | 0.106436 |
07532f5a10906c237ad3a39209766e0e40d93170 | 3,036 | py | Python | maps/views.py | WPRDC/neighborhood-simulacrum | 46892dfdbc8bc3201e31fee4ee991c49b208753e | [
"MIT"
] | null | null | null | maps/views.py | WPRDC/neighborhood-simulacrum | 46892dfdbc8bc3201e31fee4ee991c49b208753e | [
"MIT"
] | 6 | 2020-12-18T17:21:35.000Z | 2021-03-03T21:08:44.000Z | maps/views.py | WPRDC/neighborhood-simulacrum | 46892dfdbc8bc3201e31fee4ee991c49b208753e | [
"MIT"
] | null | null | null | import json
from typing import Type, TYPE_CHECKING
from django.core.exceptions import ObjectDoesNotExist
from django.utils.decorators import method_decorator
from django.views.decorators.cache import cache_page
from rest_framework import viewsets, filters
from rest_framework.exceptions import NotFound
from rest_framew... | 35.717647 | 94 | 0.745389 | 2,059 | 0.678195 | 0 | 0 | 752 | 0.247694 | 0 | 0 | 398 | 0.131094 |
0754a45f518b76cfc3fadb21e0d4b383c11aeb7f | 2,937 | py | Python | magma/operators.py | Kuree/magma | be2439aa897768c5810be72e3a55a6f772ac83cf | [
"MIT"
] | null | null | null | magma/operators.py | Kuree/magma | be2439aa897768c5810be72e3a55a6f772ac83cf | [
"MIT"
] | null | null | null | magma/operators.py | Kuree/magma | be2439aa897768c5810be72e3a55a6f772ac83cf | [
"MIT"
] | null | null | null | from magma import _BitType, BitType, BitsType, UIntType, SIntType
class MantleImportError(RuntimeError):
pass
class UndefinedOperatorError(RuntimeError):
pass
def raise_mantle_import_error_unary(self):
raise MantleImportError(
"Operators are not defined until mantle has been imported")
def r... | 26.459459 | 79 | 0.571672 | 99 | 0.033708 | 0 | 0 | 0 | 0 | 0 | 0 | 847 | 0.28839 |
075601d812e7788a83abdb5d69e6437c29517e9c | 7,993 | py | Python | src/sultan/result.py | bquantump/sultan | a46e8dc9b09385a7226f6151134ae2417166f25d | [
"MIT"
] | null | null | null | src/sultan/result.py | bquantump/sultan | a46e8dc9b09385a7226f6151134ae2417166f25d | [
"MIT"
] | null | null | null | src/sultan/result.py | bquantump/sultan | a46e8dc9b09385a7226f6151134ae2417166f25d | [
"MIT"
] | null | null | null | import subprocess
import sys
import time
import traceback
from queue import Queue
from sultan.core import Base
from sultan.echo import Echo
from threading import Thread
class Result(Base):
"""
Class that encompasses the result of a POpen command.
"""
def __init__(self, process, commands, context, st... | 31.222656 | 110 | 0.555236 | 7,820 | 0.978356 | 0 | 0 | 1,662 | 0.207932 | 0 | 0 | 1,700 | 0.212686 |
07565d1f240205eff7e6a9514e645e53e8414dbd | 10,991 | py | Python | great_expectations/cli/datasource.py | orenovadia/great_expectations | 76ef0c4e066227f8b589a1ee6ac885618f65906e | [
"Apache-2.0"
] | null | null | null | great_expectations/cli/datasource.py | orenovadia/great_expectations | 76ef0c4e066227f8b589a1ee6ac885618f65906e | [
"Apache-2.0"
] | null | null | null | great_expectations/cli/datasource.py | orenovadia/great_expectations | 76ef0c4e066227f8b589a1ee6ac885618f65906e | [
"Apache-2.0"
] | null | null | null | import os
import click
from .util import cli_message
from great_expectations.render import DefaultJinjaPageView
from great_expectations.version import __version__ as __version__
def add_datasource(context):
cli_message(
"""
========== Datasources ==========
See <blue>https://docs.greatexpectations.io/en... | 38.837456 | 180 | 0.655263 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5,425 | 0.493586 |
0756766e6e04859ce22940229b15353362178faa | 4,105 | py | Python | python/crawler/downloader.py | rgb-24bit/code-library | 8da8336e241e1428b2b46c6939bd5e9eadcf3e68 | [
"MIT"
] | null | null | null | python/crawler/downloader.py | rgb-24bit/code-library | 8da8336e241e1428b2b46c6939bd5e9eadcf3e68 | [
"MIT"
] | null | null | null | python/crawler/downloader.py | rgb-24bit/code-library | 8da8336e241e1428b2b46c6939bd5e9eadcf3e68 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Provide download function by request
"""
from datetime import datetime
import logging
import time
import urllib.parse
import requests
from bs4 import BeautifulSoup
class Throttle(object):
"""Throttle downloading by sleeping between requests to same domain."""
de... | 37.66055 | 81 | 0.599026 | 3,885 | 0.946407 | 0 | 0 | 0 | 0 | 0 | 0 | 858 | 0.209013 |
07571f5303eed07dcbb7a47a5145eef3cd7c884f | 536 | py | Python | medium/151.py | pisskidney/leetcode | 08c19cbf3d7afc897908ea05db4ad11a5487f523 | [
"MIT"
] | null | null | null | medium/151.py | pisskidney/leetcode | 08c19cbf3d7afc897908ea05db4ad11a5487f523 | [
"MIT"
] | null | null | null | medium/151.py | pisskidney/leetcode | 08c19cbf3d7afc897908ea05db4ad11a5487f523 | [
"MIT"
] | null | null | null | #!/usr/bin/python
class Solution(object):
def reverseWords(self, s):
if s == '':
return s
res = []
i = len(s) - 2
while i >= -1:
if s[i] == ' ' or i == -1:
word = ''
j = i + 1
while j < len(s) and s[j] != ' ':
... | 20.615385 | 49 | 0.33209 | 469 | 0.875 | 0 | 0 | 0 | 0 | 0 | 0 | 35 | 0.065299 |
07573778dc31fb4c60d28d2030387a7be8144f36 | 7,327 | py | Python | src/keycloak/connection.py | ecederstrand/python-keycloak | 77686a2764a3fcba092d78e02f42a58c7214c30e | [
"MIT"
] | null | null | null | src/keycloak/connection.py | ecederstrand/python-keycloak | 77686a2764a3fcba092d78e02f42a58c7214c30e | [
"MIT"
] | null | null | null | src/keycloak/connection.py | ecederstrand/python-keycloak | 77686a2764a3fcba092d78e02f42a58c7214c30e | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
#
# The MIT License (MIT)
#
# Copyright (C) 2017 Marcos Pereira <marcospereira.mpj@gmail.com>
#
# 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, in... | 32.564444 | 88 | 0.608162 | 5,947 | 0.811656 | 0 | 0 | 849 | 0.115873 | 0 | 0 | 3,622 | 0.494336 |
07577b638bc8a39bd8fcb86c2ed5cc924e43d86a | 700 | py | Python | 2020/23.py | Valokoodari/advent-of-code | c664987f739e0b07ddad34bad87d56768556a5a5 | [
"MIT"
] | 2 | 2021-12-27T18:59:11.000Z | 2022-01-10T02:31:36.000Z | 2020/23.py | Valokoodari/advent-of-code-2019 | c664987f739e0b07ddad34bad87d56768556a5a5 | [
"MIT"
] | null | null | null | 2020/23.py | Valokoodari/advent-of-code-2019 | c664987f739e0b07ddad34bad87d56768556a5a5 | [
"MIT"
] | 2 | 2021-12-23T17:29:10.000Z | 2021-12-24T03:21:49.000Z | #!venv/bin/python3
cs = [int(c) for c in open("inputs/23.in", "r").readline().strip()]
def f(cs, ts):
p,cc = {n: cs[(i+1)%len(cs)] for i,n in enumerate(cs)},cs[-1]
for _ in range(ts):
cc,dc = p[cc],p[cc]-1 if p[cc]-1 > 0 else max(p.keys())
hc,p[cc] = [p[cc], p[p[cc]], p[p[p[cc]]]],p[p[p[p[cc]]... | 29.166667 | 77 | 0.452857 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 55 | 0.078571 |
07579f83aea9f0c480c258cdf19ac53f9ebbfd10 | 160 | py | Python | run.py | jakewright/home-automation-device-registry | b073966b1dc259a6997c47f8d369f51dee9cbbf3 | [
"MIT"
] | 15 | 2018-01-09T21:57:09.000Z | 2021-05-08T10:23:01.000Z | run.py | jakewright/home-automation-device-registry | b073966b1dc259a6997c47f8d369f51dee9cbbf3 | [
"MIT"
] | null | null | null | run.py | jakewright/home-automation-device-registry | b073966b1dc259a6997c47f8d369f51dee9cbbf3 | [
"MIT"
] | 10 | 2018-09-23T20:30:24.000Z | 2021-05-08T10:23:02.000Z | # Import the application
from device_registry import app
# Run the application in debug mode
app.run(host='0.0.0.0', port=int(app.config['PORT']), debug=True)
| 26.666667 | 65 | 0.74375 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 74 | 0.4625 |
0758c8b4614be9ea14ff7452e9accfcfb90b432b | 1,263 | py | Python | dvc/utils/stage.py | Abrosimov-a-a/dvc | 93280c937b9160003afb0d2f3fd473c03d6d9673 | [
"Apache-2.0"
] | null | null | null | dvc/utils/stage.py | Abrosimov-a-a/dvc | 93280c937b9160003afb0d2f3fd473c03d6d9673 | [
"Apache-2.0"
] | null | null | null | dvc/utils/stage.py | Abrosimov-a-a/dvc | 93280c937b9160003afb0d2f3fd473c03d6d9673 | [
"Apache-2.0"
] | null | null | null | import yaml
from ruamel.yaml import YAML
from ruamel.yaml.error import YAMLError
try:
from yaml import CSafeLoader as SafeLoader
except ImportError:
from yaml import SafeLoader
from dvc.exceptions import StageFileCorruptedError
from dvc.utils.compat import open
def load_stage_file(path):
with open(path,... | 26.87234 | 76 | 0.69517 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 323 | 0.25574 |
075a282b1afd93e2cc9af2acd58c24b3702f7904 | 93 | py | Python | CAMPODETIRO/test.py | Arguel/old-projects | 2e5f594a6303b2e137acf555569eca98aab08054 | [
"Apache-2.0"
] | null | null | null | CAMPODETIRO/test.py | Arguel/old-projects | 2e5f594a6303b2e137acf555569eca98aab08054 | [
"Apache-2.0"
] | null | null | null | CAMPODETIRO/test.py | Arguel/old-projects | 2e5f594a6303b2e137acf555569eca98aab08054 | [
"Apache-2.0"
] | null | null | null | entrada = input("palabra")
listaDeLetras = []
for i in entrada:
listaDeLetras.append(i)
| 15.5 | 27 | 0.698925 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 0.096774 |
075a46f6df538e13d87e3247bc8ca4b6d54f0b7b | 659 | py | Python | demos/nn_classification_demo.py | fire-breathing-rubber-lemons/cs207-FinalProject | 92d1d7d70637e2478effb01c9ce56199e0f873c9 | [
"MIT"
] | null | null | null | demos/nn_classification_demo.py | fire-breathing-rubber-lemons/cs207-FinalProject | 92d1d7d70637e2478effb01c9ce56199e0f873c9 | [
"MIT"
] | 31 | 2019-10-18T16:14:07.000Z | 2019-12-10T16:38:34.000Z | demos/nn_classification_demo.py | fire-breathing-rubber-lemons/cs207-FinalProject | 92d1d7d70637e2478effb01c9ce56199e0f873c9 | [
"MIT"
] | null | null | null | import numpy as np
from pyad.nn import NeuralNet
from sklearn.datasets import load_breast_cancer
from sklearn.model_selection import train_test_split
np.random.seed(0)
data = load_breast_cancer()
X_train, X_test, y_train, y_test = train_test_split(
data.data, data.target, train_size=0.8, random_state=0
)
nn = Ne... | 26.36 | 59 | 0.76176 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 55 | 0.08346 |
075c40bff74b1c9ad80e482ccef0c574552a2c97 | 226 | py | Python | mgatemp.py | zobclub/chapter8 | fbd9e8711747b7446f75b472bae1465fe0ab495c | [
"MIT"
] | 1 | 2021-12-02T10:56:49.000Z | 2021-12-02T10:56:49.000Z | mgatemp.py | zobclub/chapter8 | fbd9e8711747b7446f75b472bae1465fe0ab495c | [
"MIT"
] | null | null | null | mgatemp.py | zobclub/chapter8 | fbd9e8711747b7446f75b472bae1465fe0ab495c | [
"MIT"
] | null | null | null | from microbit import *
I2CADR = 0x0E
DIE_TEMP = 0x0F
while True:
i2c.write(I2CADR, bytearray([DIE_TEMP]))
d = i2c.read(I2CADR, 1)
x = d[0]
if x >=128:
x -= 256
x += 10
print(x)
sleep(500) | 16.142857 | 44 | 0.553097 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
075cb80186092395148f9c03498c024c22cfd0b5 | 793 | py | Python | utils/nlp.py | splovyt/SFPython-Project-Night | 50f20f581e074401d59d91457bac2a69631bef61 | [
"Apache-2.0"
] | 1 | 2019-04-17T18:02:59.000Z | 2019-04-17T18:02:59.000Z | utils/nlp.py | splovyt/SFPython-Project-Night | 50f20f581e074401d59d91457bac2a69631bef61 | [
"Apache-2.0"
] | null | null | null | utils/nlp.py | splovyt/SFPython-Project-Night | 50f20f581e074401d59d91457bac2a69631bef61 | [
"Apache-2.0"
] | null | null | null | import ssl
import nltk
from textblob import TextBlob
from nltk.corpus import stopwords
# set SSL
try:
_create_unverified_https_context = ssl._create_unverified_context
except AttributeError:
pass
else:
ssl._create_default_https_context = _create_unverified_https_context
# download noun data (if required... | 26.433333 | 98 | 0.760404 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 214 | 0.269861 |
075cf0dd079f839e7d44c9491837f8a19123cdd5 | 1,418 | py | Python | toolbox/core/management/commands/celery_beat_resource_scraper.py | akshedu/toolbox | 7c647433b68f1098ee4c8623f836f74785dc970c | [
"MIT"
] | null | null | null | toolbox/core/management/commands/celery_beat_resource_scraper.py | akshedu/toolbox | 7c647433b68f1098ee4c8623f836f74785dc970c | [
"MIT"
] | null | null | null | toolbox/core/management/commands/celery_beat_resource_scraper.py | akshedu/toolbox | 7c647433b68f1098ee4c8623f836f74785dc970c | [
"MIT"
] | null | null | null |
from django_celery_beat.models import PeriodicTask, IntervalSchedule
from django.core.management.base import BaseCommand
from django.db import IntegrityError
class Command(BaseCommand):
def handle(self, *args, **options):
try:
schedule_channel, created = IntervalSchedule.objects.get_or_create... | 32.227273 | 79 | 0.499295 | 1,254 | 0.884344 | 0 | 0 | 0 | 0 | 0 | 0 | 124 | 0.087447 |
075ee89278e2e099ce3c9cbc108dfe159e2012f2 | 3,284 | py | Python | ppcls/data/preprocess/__init__.py | zhusonghe/PaddleClas-1 | e2e492f9c78ed5084cc50d7c45eef4cc41e1eeaf | [
"Apache-2.0"
] | 3,763 | 2020-04-10T04:48:11.000Z | 2022-03-31T13:24:37.000Z | ppcls/data/preprocess/__init__.py | zhusonghe/PaddleClas-1 | e2e492f9c78ed5084cc50d7c45eef4cc41e1eeaf | [
"Apache-2.0"
] | 633 | 2020-04-08T18:27:31.000Z | 2022-03-31T01:09:43.000Z | ppcls/data/preprocess/__init__.py | zhusonghe/PaddleClas-1 | e2e492f9c78ed5084cc50d7c45eef4cc41e1eeaf | [
"Apache-2.0"
] | 846 | 2020-04-08T08:13:18.000Z | 2022-03-31T12:28:37.000Z | # Copyright (c) 2021 PaddlePaddle 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 appli... | 32.514851 | 114 | 0.715286 | 1,438 | 0.437881 | 0 | 0 | 0 | 0 | 0 | 0 | 799 | 0.243301 |
075fafdab69c5858ee27f6483fe78f36b26b216c | 11,121 | py | Python | src/scalar_net/visualisations.py | scheeloong/lindaedynamics_icml2018 | d03b450e254d33b019161a3cd015e44aafe407cb | [
"MIT"
] | 1 | 2018-08-04T17:04:13.000Z | 2018-08-04T17:04:13.000Z | src/scalar_net/visualisations.py | scheeloong/lindaedynamics_icml2018 | d03b450e254d33b019161a3cd015e44aafe407cb | [
"MIT"
] | null | null | null | src/scalar_net/visualisations.py | scheeloong/lindaedynamics_icml2018 | d03b450e254d33b019161a3cd015e44aafe407cb | [
"MIT"
] | null | null | null | # required modules
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from matplotlib import cm
from matplotlib.colors import Normalize
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.animation import FuncAnimation
# two-dimesional version
def plot_mse_loss_surface_2d(fi... | 35.193038 | 103 | 0.608488 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,742 | 0.156641 |
075fc7c73e1c7b1fe3355a9a233cd8869299a19e | 7,435 | py | Python | tests/qconvolutional_test.py | kshithijiyer/qkeras | 78ac608c6dcd84151792a986d03fe7afb17929cf | [
"Apache-2.0"
] | null | null | null | tests/qconvolutional_test.py | kshithijiyer/qkeras | 78ac608c6dcd84151792a986d03fe7afb17929cf | [
"Apache-2.0"
] | null | null | null | tests/qconvolutional_test.py | kshithijiyer/qkeras | 78ac608c6dcd84151792a986d03fe7afb17929cf | [
"Apache-2.0"
] | null | null | null | # Copyright 2019 Google LLC
#
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,... | 33.490991 | 80 | 0.646537 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,732 | 0.232952 |
076073f7df321e46ea5bd065cc9331746695ec1f | 2,356 | py | Python | discord/ext/ui/select.py | Lapis256/discord-ext-ui | 593de0a1107d2a0c26023587a2937f00ecec3ed1 | [
"MIT"
] | null | null | null | discord/ext/ui/select.py | Lapis256/discord-ext-ui | 593de0a1107d2a0c26023587a2937f00ecec3ed1 | [
"MIT"
] | null | null | null | discord/ext/ui/select.py | Lapis256/discord-ext-ui | 593de0a1107d2a0c26023587a2937f00ecec3ed1 | [
"MIT"
] | null | null | null | from typing import Optional, List, TypeVar, Generic, Callable
import discord.ui
from .item import Item
from .select_option import SelectOption
from .custom import CustomSelect
def _default_check(_: discord.Interaction) -> bool:
return True
C = TypeVar("C", bound=discord.ui.Select)
class Select(Item, Generic... | 28.731707 | 79 | 0.61163 | 2,061 | 0.874788 | 0 | 0 | 0 | 0 | 0 | 0 | 67 | 0.028438 |
0760aecd744d04b7a42ae02e90ca8b423ee0a619 | 2,834 | py | Python | ucscsdk/mometa/storage/StorageScsiLunRef.py | parag-may4/ucscsdk | 2ea762fa070330e3a4e2c21b46b157469555405b | [
"Apache-2.0"
] | 9 | 2016-12-22T08:39:25.000Z | 2019-09-10T15:36:19.000Z | ucscsdk/mometa/storage/StorageScsiLunRef.py | parag-may4/ucscsdk | 2ea762fa070330e3a4e2c21b46b157469555405b | [
"Apache-2.0"
] | 10 | 2017-01-31T06:59:56.000Z | 2021-11-09T09:14:37.000Z | ucscsdk/mometa/storage/StorageScsiLunRef.py | parag-may4/ucscsdk | 2ea762fa070330e3a4e2c21b46b157469555405b | [
"Apache-2.0"
] | 13 | 2016-11-14T07:42:58.000Z | 2022-02-10T17:32:05.000Z | """This module contains the general information for StorageScsiLunRef ManagedObject."""
from ...ucscmo import ManagedObject
from ...ucsccoremeta import UcscVersion, MoPropertyMeta, MoMeta
from ...ucscmeta import VersionMeta
class StorageScsiLunRefConsts():
pass
class StorageScsiLunRef(ManagedObject):
"""Th... | 50.607143 | 251 | 0.642202 | 2,602 | 0.918137 | 0 | 0 | 0 | 0 | 0 | 0 | 933 | 0.329217 |
0761a4f4179e9679d7d567a51af6174207abac78 | 16,697 | py | Python | saxstools/fullsaxs.py | latrocinia/saxstools | 8e88474f62466b745791c0ccbb07c80a959880f3 | [
"Python-2.0",
"OLDAP-2.7"
] | null | null | null | saxstools/fullsaxs.py | latrocinia/saxstools | 8e88474f62466b745791c0ccbb07c80a959880f3 | [
"Python-2.0",
"OLDAP-2.7"
] | null | null | null | saxstools/fullsaxs.py | latrocinia/saxstools | 8e88474f62466b745791c0ccbb07c80a959880f3 | [
"Python-2.0",
"OLDAP-2.7"
] | null | null | null | from __future__ import print_function, absolute_import, division
from sys import stdout as _stdout
from time import time as _time
import numpy as np
try:
import pyfftw
pyfftw.interfaces.cache.enable()
pyfftw.interfaces.cache.set_keepalive_time(10)
rfftn = pyfftw.interfaces.numpy_fft.rfftn
irfftn =... | 32.675147 | 115 | 0.581302 | 14,025 | 0.839971 | 0 | 0 | 2,180 | 0.130562 | 0 | 0 | 3,230 | 0.193448 |
0762390f8b5995d6cf171f62842c5c4b8e02141e | 985 | py | Python | lib/generate_random_obs.py | zehuilu/Learning-from-Sparse-Demonstrations | 4d652635c24f847fe51bc050773762b549ce41c0 | [
"MIT"
] | 8 | 2020-08-16T00:09:57.000Z | 2021-09-24T00:58:46.000Z | lib/generate_random_obs.py | zehuilu/Learning-from-Sparse-Demonstrations | 4d652635c24f847fe51bc050773762b549ce41c0 | [
"MIT"
] | null | null | null | lib/generate_random_obs.py | zehuilu/Learning-from-Sparse-Demonstrations | 4d652635c24f847fe51bc050773762b549ce41c0 | [
"MIT"
] | 2 | 2021-01-26T02:33:13.000Z | 2021-08-25T01:52:07.000Z | #!/usr/bin/env python3
import os
import sys
import time
sys.path.append(os.getcwd()+'/lib')
import random
from dataclasses import dataclass, field
from ObsInfo import ObsInfo
def generate_random_obs(num_obs: int, size_list: list, config_data):
"""
config_file_name = "config.json"
json_file = open(config_f... | 30.78125 | 131 | 0.658883 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 367 | 0.372589 |
07629f29c3ccce164edffac5aaf1f19ce3ce8456 | 6,934 | py | Python | userbot/helper_funcs/misc.py | Abucuyy/Uciha | 726e9cd61eabf056064e40f7b322d8993161e52a | [
"Naumen",
"Condor-1.1",
"MS-PL"
] | null | null | null | userbot/helper_funcs/misc.py | Abucuyy/Uciha | 726e9cd61eabf056064e40f7b322d8993161e52a | [
"Naumen",
"Condor-1.1",
"MS-PL"
] | 1 | 2021-02-08T20:43:56.000Z | 2021-02-08T20:43:56.000Z | userbot/helper_funcs/misc.py | Abucuyy/Uciha | 726e9cd61eabf056064e40f7b322d8993161e52a | [
"Naumen",
"Condor-1.1",
"MS-PL"
] | 5 | 2020-09-05T12:45:31.000Z | 2020-09-25T09:04:29.000Z | # TG-UserBot - A modular Telegram UserBot script for Python.
# Copyright (C) 2019 Kandarp <https://github.com/kandnub>
#
# TG-UserBot 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 t... | 37.27957 | 80 | 0.608595 | 0 | 0 | 0 | 0 | 0 | 0 | 5,124 | 0.738967 | 2,065 | 0.297808 |
0763811316d721bd61d00c534d919a140fb4b71a | 1,421 | py | Python | gym-multilayerthinfilm/utils.py | HarryTheBird/gym-multilayerthinfilm | 22eda96e71e95e9ea1b491fae633c4a32fadb023 | [
"MIT"
] | 10 | 2021-05-20T19:46:36.000Z | 2022-02-24T03:06:46.000Z | gym-multilayerthinfilm/utils.py | HarryTheBird/gym-multilayerthinfilm | 22eda96e71e95e9ea1b491fae633c4a32fadb023 | [
"MIT"
] | null | null | null | gym-multilayerthinfilm/utils.py | HarryTheBird/gym-multilayerthinfilm | 22eda96e71e95e9ea1b491fae633c4a32fadb023 | [
"MIT"
] | 2 | 2021-12-11T21:49:35.000Z | 2022-03-04T06:28:57.000Z | import numpy as np
def get_n_from_txt(filepath, points=None, lambda_min=400, lambda_max=700, complex_n=True):
ntxt = np.loadtxt(filepath)
if np.min(np.abs(ntxt[:, 0] - lambda_min)) > 25 or np.min(np.abs(ntxt[:, 0] - lambda_max)) > 25:
print('No measurement data for refractive indicies are available wit... | 43.060606 | 113 | 0.626319 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 78 | 0.054891 |
0765d0b1f7f6046c9a5ec38c71317e234a345a45 | 270 | py | Python | pyrocco/__init__.py | joaopalmeiro/pyrocco | 4144f56d654500c3ec49cb04c06b98296004eafe | [
"MIT"
] | null | null | null | pyrocco/__init__.py | joaopalmeiro/pyrocco | 4144f56d654500c3ec49cb04c06b98296004eafe | [
"MIT"
] | 4 | 2021-05-31T16:44:16.000Z | 2021-05-31T17:08:04.000Z | pyrocco/__init__.py | joaopalmeiro/pyrocco | 4144f56d654500c3ec49cb04c06b98296004eafe | [
"MIT"
] | null | null | null | __package_name__ = "pyrocco"
__version__ = "0.1.0"
__author__ = "João Palmeiro"
__author_email__ = "jm.palmeiro@campus.fct.unl.pt"
__description__ = "A Python CLI to add the Party Parrot to a custom background image."
__url__ = "https://github.com/joaopalmeiro/pyrocco"
| 38.571429 | 86 | 0.766667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 172 | 0.634686 |
0768b4de117d71513a10b4439456e7226bc8f05f | 850 | py | Python | 2020/day08/machine.py | ingjrs01/adventofcode | c5e4f0158dac0efc2dbfc10167f2700693b41fea | [
"Apache-2.0"
] | null | null | null | 2020/day08/machine.py | ingjrs01/adventofcode | c5e4f0158dac0efc2dbfc10167f2700693b41fea | [
"Apache-2.0"
] | null | null | null | 2020/day08/machine.py | ingjrs01/adventofcode | c5e4f0158dac0efc2dbfc10167f2700693b41fea | [
"Apache-2.0"
] | null | null | null | class Machine():
def __init__(self):
self.pointer = 0
self.accum = 0
self.visited = []
def run(self,program):
salir = False
while (salir == False):
if (self.pointer in self.visited):
return False
if (self.pointer >= len(progr... | 22.368421 | 54 | 0.483529 | 843 | 0.991765 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 0.011765 |
0768ed6923c47dbe150e783f6cd01fa2f7c9e54c | 41 | py | Python | EduData/Task/__init__.py | BAOOOOOM/EduData | affa465779cb94db00ed19291f8411229d342c0f | [
"Apache-2.0"
] | 98 | 2019-07-05T03:27:36.000Z | 2022-03-30T08:38:09.000Z | EduData/Task/__init__.py | BAOOOOOM/EduData | affa465779cb94db00ed19291f8411229d342c0f | [
"Apache-2.0"
] | 45 | 2020-12-25T03:49:43.000Z | 2021-11-26T09:45:42.000Z | EduData/Task/__init__.py | BAOOOOOM/EduData | affa465779cb94db00ed19291f8411229d342c0f | [
"Apache-2.0"
] | 50 | 2019-08-17T05:11:15.000Z | 2022-03-29T07:54:13.000Z | # coding: utf-8
# 2019/8/23 @ tongshiwei
| 13.666667 | 24 | 0.658537 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 39 | 0.95122 |
076975f577d6632b0b1b26b10892f5123c387c67 | 1,286 | py | Python | 010-round.py | richardvecsey/python-basics | b66abef77bce2ddd6f2f39b631e1dd97a9aa2fac | [
"MIT"
] | 3 | 2019-12-29T18:52:21.000Z | 2020-02-20T09:18:08.000Z | 010-round.py | richardvecsey/python-basics | b66abef77bce2ddd6f2f39b631e1dd97a9aa2fac | [
"MIT"
] | null | null | null | 010-round.py | richardvecsey/python-basics | b66abef77bce2ddd6f2f39b631e1dd97a9aa2fac | [
"MIT"
] | 2 | 2020-02-20T09:18:13.000Z | 2020-06-04T04:51:44.000Z | """
Round a number
--------------
Input (float) A floating point number
(int) Number of decimals
Default value is: 0
Output (float) Rounded number
(int) Whether using the default decimals value, the return number
will be the nearest ... | 33.842105 | 80 | 0.64619 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 795 | 0.618196 |
076ab2cb67c5bd176123d8332c42ca379bbe81d8 | 992 | py | Python | service.py | Kleist/MusicPlayer | 95f634d1e4d47e7b430e32ad9224d94ad0453c82 | [
"MIT"
] | 1 | 2020-08-14T21:14:09.000Z | 2020-08-14T21:14:09.000Z | service.py | Kleist/MusicPlayer | 95f634d1e4d47e7b430e32ad9224d94ad0453c82 | [
"MIT"
] | null | null | null | service.py | Kleist/MusicPlayer | 95f634d1e4d47e7b430e32ad9224d94ad0453c82 | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
import RPi.GPIO as GPIO
from mfrc522 import SimpleMFRC522
import play
import time
class TagPlayer(object):
def __init__(self):
self._current = None
self.reader = SimpleMFRC522()
self._failed = 0
def step(self):
id, text = self.reader.read_no_block()
... | 22.545455 | 64 | 0.521169 | 713 | 0.71875 | 0 | 0 | 0 | 0 | 0 | 0 | 61 | 0.061492 |
076b099ed1e8933339bc07b3aea99e064efdee24 | 1,118 | py | Python | mypy/defaults.py | ckanesan/mypy | ffb3ce925e8bb3376e19f942c7d3a3806c9bba97 | [
"PSF-2.0"
] | null | null | null | mypy/defaults.py | ckanesan/mypy | ffb3ce925e8bb3376e19f942c7d3a3806c9bba97 | [
"PSF-2.0"
] | 8 | 2021-03-18T22:27:44.000Z | 2022-02-10T09:18:50.000Z | mypy/defaults.py | ckanesan/mypy | ffb3ce925e8bb3376e19f942c7d3a3806c9bba97 | [
"PSF-2.0"
] | 1 | 2021-09-20T06:37:41.000Z | 2021-09-20T06:37:41.000Z | import os
MYPY = False
if MYPY:
from typing_extensions import Final
PYTHON2_VERSION = (2, 7) # type: Final
PYTHON3_VERSION = (3, 6) # type: Final
PYTHON3_VERSION_MIN = (3, 4) # type: Final
CACHE_DIR = '.mypy_cache' # type: Final
CONFIG_FILE = 'mypy.ini' # type: Final
SHARED_CONFIG_FILES = ['setup.cfg', ] # ... | 34.9375 | 91 | 0.604651 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 504 | 0.450805 |
4aca7d77d6d130f3025fa754e718e7148f830e41 | 3,558 | py | Python | skcriteria/preprocessing/push_negatives.py | elcolie/scikit-criteria | 216674d699b60d68fefa98d44afd619943f3bb00 | [
"BSD-3-Clause"
] | null | null | null | skcriteria/preprocessing/push_negatives.py | elcolie/scikit-criteria | 216674d699b60d68fefa98d44afd619943f3bb00 | [
"BSD-3-Clause"
] | null | null | null | skcriteria/preprocessing/push_negatives.py | elcolie/scikit-criteria | 216674d699b60d68fefa98d44afd619943f3bb00 | [
"BSD-3-Clause"
] | null | null | null | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# License: BSD-3 (https://tldrlegal.com/license/bsd-3-clause-license-(revised))
# Copyright (c) 2016-2021, Cabral, Juan; Luczywo, Nadia
# All rights reserved.
# =============================================================================
# DOCS
# =========================... | 30.93913 | 79 | 0.522766 | 826 | 0.232153 | 0 | 0 | 309 | 0.086847 | 0 | 0 | 2,885 | 0.810849 |
4acaa4e6a8b6fa3eb236788a62a84f44c80e376f | 3,451 | py | Python | ingenico/direct/sdk/domain/customer_token.py | Ingenico/direct-sdk-python3 | d2b30b8e8afb307153a1f19ac4c054d5344449ce | [
"Apache-2.0"
] | null | null | null | ingenico/direct/sdk/domain/customer_token.py | Ingenico/direct-sdk-python3 | d2b30b8e8afb307153a1f19ac4c054d5344449ce | [
"Apache-2.0"
] | 1 | 2021-03-30T12:55:39.000Z | 2021-04-08T08:23:27.000Z | ingenico/direct/sdk/domain/customer_token.py | Ingenico/direct-sdk-python3 | d2b30b8e8afb307153a1f19ac4c054d5344449ce | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
#
# This class was auto-generated from the API references found at
# https://support.direct.ingenico.com/documentation/api/reference/
#
from ingenico.direct.sdk.data_object import DataObject
from ingenico.direct.sdk.domain.address import Address
from ingenico.direct.sdk.domain.company_informatio... | 41.578313 | 109 | 0.703854 | 3,009 | 0.871921 | 0 | 0 | 1,126 | 0.326282 | 0 | 0 | 946 | 0.274123 |
4acbbae7f94e1d806015de62ee5a96d02c3544d7 | 301 | py | Python | inserter.py | pirate/macOS-global-autocomplete | 4ba8c3efdd34e7b4c0044c50f47d21a1bafd9aac | [
"MIT"
] | 23 | 2018-12-28T17:33:33.000Z | 2022-03-07T21:25:31.000Z | inserter.py | pirate/osx-global-autocomplete | 4ba8c3efdd34e7b4c0044c50f47d21a1bafd9aac | [
"MIT"
] | null | null | null | inserter.py | pirate/osx-global-autocomplete | 4ba8c3efdd34e7b4c0044c50f47d21a1bafd9aac | [
"MIT"
] | 2 | 2017-02-27T18:08:12.000Z | 2018-08-27T00:40:10.000Z | import time
import pykeyboard
# TODO: Replace following two lines with the code that activate the application.
print('Activate the application 3 seconds.')
time.sleep(3)
k = pykeyboard.PyKeyboard()
k.press_key(k.left_key)
time.sleep(1) # Hold down left key for 1 second.
k.release_key(k.left_key)
| 21.5 | 80 | 0.770764 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 151 | 0.501661 |
4acbd0cbd7b35addaf03f24e1fa4d33805db8c3a | 4,819 | py | Python | tools/corpora.py | EleutherAI/megatron-3d | be3014d47a127f08871d0ba6d6389363f2484397 | [
"MIT"
] | 3 | 2021-02-13T21:51:45.000Z | 2021-02-14T23:15:02.000Z | tools/corpora.py | EleutherAI/megatron-3d | be3014d47a127f08871d0ba6d6389363f2484397 | [
"MIT"
] | 13 | 2021-02-08T11:22:38.000Z | 2021-02-18T20:13:10.000Z | tools/corpora.py | EleutherAI/megatron-3d | be3014d47a127f08871d0ba6d6389363f2484397 | [
"MIT"
] | 2 | 2021-02-13T22:13:21.000Z | 2021-10-12T06:39:33.000Z | import os
import tarfile
from abc import ABC, abstractmethod
from glob import glob
import shutil
import random
import zstandard
"""
This registry is for automatically downloading and extracting datasets.
To register a class you need to inherit the DataDownloader class, provide name, filetype and url attributes, and
(... | 35.175182 | 136 | 0.661756 | 3,260 | 0.676489 | 0 | 0 | 393 | 0.081552 | 0 | 0 | 1,722 | 0.357336 |
4acced6bfbc482f9d38f37f561868a587991d47b | 1,575 | py | Python | othello_rl/qlearning/qlearning.py | aka256/othello-rl | ef5e78c6cf6b276e16b50086b53138ab968d728c | [
"MIT"
] | null | null | null | othello_rl/qlearning/qlearning.py | aka256/othello-rl | ef5e78c6cf6b276e16b50086b53138ab968d728c | [
"MIT"
] | null | null | null | othello_rl/qlearning/qlearning.py | aka256/othello-rl | ef5e78c6cf6b276e16b50086b53138ab968d728c | [
"MIT"
] | null | null | null | from logging import getLogger
logger = getLogger(__name__)
class QLearning:
"""
Q-Learning用のクラス
Attributes
----------
alpha : float
学習率α
gamma : float
割引率γ
data : dict
Q-Learningでの学習結果の保存用辞書
init_value : float
dataの初期値
"""
def __init__(self, alpha: float, gamma: float, data: dict ... | 17.119565 | 98 | 0.507937 | 1,649 | 0.963764 | 0 | 0 | 0 | 0 | 0 | 0 | 949 | 0.554646 |
4acdb07fa21e6d09ec1006ea9fc4f7c0e59b102d | 6,748 | py | Python | SearchService/test/unit/test_solr_interface.py | loftwah/appscale | 586fc1347ebc743d7a632de698f4dbfb09ae38d6 | [
"Apache-2.0"
] | 790 | 2015-01-03T02:13:39.000Z | 2020-05-10T19:53:57.000Z | SearchService/test/unit/test_solr_interface.py | loftwah/appscale | 586fc1347ebc743d7a632de698f4dbfb09ae38d6 | [
"Apache-2.0"
] | 1,361 | 2015-01-08T23:09:40.000Z | 2020-04-14T00:03:04.000Z | SearchService/test/unit/test_solr_interface.py | loftwah/appscale | 586fc1347ebc743d7a632de698f4dbfb09ae38d6 | [
"Apache-2.0"
] | 155 | 2015-01-08T22:59:31.000Z | 2020-04-08T08:01:53.000Z | #!/usr/bin/env python
import os
import json
import sys
import unittest
import urllib2
from flexmock import flexmock
sys.path.append(os.path.join(os.path.dirname(__file__), "../../"))
import solr_interface
import search_exceptions
class FakeSolrDoc():
def __init__(self):
self.fields = []
class FakeDocument():... | 33.405941 | 80 | 0.678275 | 6,499 | 0.9631 | 0 | 0 | 0 | 0 | 0 | 0 | 1,303 | 0.193094 |
4acdd598615906ddfbcd01ae7441ccbc9e89653b | 899 | py | Python | payabbhi/error.py | ppm-avinder/payabbhi-python | 0f84f01349e365753f4b83eee584618e1a855567 | [
"MIT"
] | 1 | 2018-03-06T08:30:38.000Z | 2018-03-06T08:30:38.000Z | payabbhi/error.py | ppm-avinder/payabbhi-python | 0f84f01349e365753f4b83eee584618e1a855567 | [
"MIT"
] | null | null | null | payabbhi/error.py | ppm-avinder/payabbhi-python | 0f84f01349e365753f4b83eee584618e1a855567 | [
"MIT"
] | 5 | 2018-10-08T05:56:44.000Z | 2020-05-22T11:31:07.000Z | class PayabbhiError(Exception):
def __init__(self, description=None, http_status=None,
field=None):
self.description = description
self.http_status = http_status
self.field = field
self._message = self.error_message()
super(PayabbhiError, self).__init__(self... | 22.475 | 90 | 0.669633 | 880 | 0.978865 | 0 | 0 | 0 | 0 | 0 | 0 | 41 | 0.045606 |
4ace0f44b44658df4422d4f5661978d41ce06350 | 1,923 | py | Python | src/mpu/__init__.py | TsinghuaAI/CPM-2-Pretrain | 33003865239e7ba13a12aabf9ec2735cef66bf3b | [
"MIT"
] | 54 | 2021-06-17T09:05:11.000Z | 2022-03-18T09:12:14.000Z | src/mpu/__init__.py | TsinghuaAI/CPM-2-Pretrain | 33003865239e7ba13a12aabf9ec2735cef66bf3b | [
"MIT"
] | 25 | 2021-06-29T02:58:28.000Z | 2022-03-30T04:45:06.000Z | src/mpu/__init__.py | TsinghuaAI/CPM-2-Pretrain | 33003865239e7ba13a12aabf9ec2735cef66bf3b | [
"MIT"
] | 11 | 2021-06-22T08:00:25.000Z | 2022-03-04T05:41:50.000Z | # coding=utf-8
# Copyright (c) 2019, NVIDIA CORPORATION. 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 re... | 36.980769 | 74 | 0.841914 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 650 | 0.338014 |
4ace72273e1ae90dc1c68aa24e3b23afcdc01695 | 2,141 | py | Python | djangosige/apps/cadastro/models/empresa.py | MateusMolina/lunoERP | 0880adb93b3a2d3169c6780efa60a229272f927a | [
"MIT"
] | null | null | null | djangosige/apps/cadastro/models/empresa.py | MateusMolina/lunoERP | 0880adb93b3a2d3169c6780efa60a229272f927a | [
"MIT"
] | null | null | null | djangosige/apps/cadastro/models/empresa.py | MateusMolina/lunoERP | 0880adb93b3a2d3169c6780efa60a229272f927a | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
import os
from django.db import models
from django.db.models.signals import post_delete
from django.dispatch import receiver
from .base import Pessoa
from djangosige.apps.login.models import Usuario
from djangosige.configs.settings import MEDIA_ROOT
def logo_directory_path(inst... | 32.439394 | 105 | 0.666978 | 1,350 | 0.630546 | 0 | 0 | 442 | 0.206446 | 0 | 0 | 300 | 0.140121 |
4acea4b00d95238388dfdf1bfda34fd153268c2f | 5,858 | py | Python | WDJN/eval/eval.py | silverriver/Stylized_Dialog | 559dd97c4ec9c91e94deb048f789684ef3f1f9fa | [
"MIT"
] | 21 | 2020-12-16T08:53:38.000Z | 2022-01-21T09:08:55.000Z | WDJN/eval/eval.py | silverriver/Stylized_Dialog | 559dd97c4ec9c91e94deb048f789684ef3f1f9fa | [
"MIT"
] | 1 | 2020-12-27T07:56:01.000Z | 2020-12-30T05:13:11.000Z | WDJN/eval/eval.py | silverriver/Stylized_Dialog | 559dd97c4ec9c91e94deb048f789684ef3f1f9fa | [
"MIT"
] | 1 | 2022-02-28T12:19:19.000Z | 2022-02-28T12:19:19.000Z | import os
from nltk.translate.bleu_score import corpus_bleu
from nltk.translate.bleu_score import SmoothingFunction
import json
from tqdm import tqdm, trange
from random import sample
import numpy as np
import pickle
import argparse
import bert_eval_acc
import svm_eval_acc
smooth = SmoothingFunction()
def eval_bleu... | 32.726257 | 118 | 0.602083 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,406 | 0.240014 |
4acf75fbdd9f5684eaa634c30e9274299d052baa | 804 | py | Python | homeassistant/components/unifi/const.py | olbjan/home-assistant-1 | 1adb45f74e96fc5eff137a3727647a7e428e123c | [
"Apache-2.0"
] | 7 | 2019-02-07T14:14:12.000Z | 2019-07-28T06:56:10.000Z | homeassistant/components/unifi/const.py | olbjan/home-assistant-1 | 1adb45f74e96fc5eff137a3727647a7e428e123c | [
"Apache-2.0"
] | 6 | 2021-02-08T20:54:31.000Z | 2022-03-12T00:50:43.000Z | homeassistant/components/unifi/const.py | olbjan/home-assistant-1 | 1adb45f74e96fc5eff137a3727647a7e428e123c | [
"Apache-2.0"
] | 1 | 2020-09-23T16:41:16.000Z | 2020-09-23T16:41:16.000Z | """Constants for the UniFi component."""
import logging
LOGGER = logging.getLogger(__package__)
DOMAIN = "unifi"
CONTROLLER_ID = "{host}-{site}"
CONF_CONTROLLER = "controller"
CONF_SITE_ID = "site"
UNIFI_WIRELESS_CLIENTS = "unifi_wireless_clients"
CONF_ALLOW_BANDWIDTH_SENSORS = "allow_bandwidth_sensors"
CONF_BLOCK... | 25.935484 | 56 | 0.823383 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 255 | 0.317164 |
4acfa6e08c91d6cf965af047f2b0bfd2e83e88a1 | 503 | py | Python | coding_intereview/1656. Design an Ordered Stream.py | Jahidul007/Python-Bootcamp | 3c870587465ff66c2c1871c8d3c4eea72463abda | [
"MIT"
] | 2 | 2020-12-07T16:07:07.000Z | 2020-12-07T16:08:53.000Z | coding_intereview/1656. Design an Ordered Stream.py | Jahidul007/Python-Bootcamp | 3c870587465ff66c2c1871c8d3c4eea72463abda | [
"MIT"
] | null | null | null | coding_intereview/1656. Design an Ordered Stream.py | Jahidul007/Python-Bootcamp | 3c870587465ff66c2c1871c8d3c4eea72463abda | [
"MIT"
] | 1 | 2020-10-03T16:38:02.000Z | 2020-10-03T16:38:02.000Z | class OrderedStream:
def __init__(self, n: int):
self.data = [None]*n
self.ptr = 0
def insert(self, id: int, value: str) -> List[str]:
id -= 1
self.data[id] = value
if id > self.ptr: return []
while self.ptr < len(self.data) and self.data[self.ptr]: ... | 26.473684 | 80 | 0.584493 | 373 | 0.741551 | 0 | 0 | 0 | 0 | 0 | 0 | 124 | 0.246521 |
4acfc9cbd59d86d35555e057b3b06babb6b17219 | 1,091 | py | Python | python/test/test_tree_dp.py | EQt/treelas | 24a5cebf101180822198806c0a4131b0efb7a36d | [
"MIT"
] | 3 | 2020-06-18T13:31:26.000Z | 2021-04-05T17:42:56.000Z | python/test/test_tree_dp.py | EQt/treelas | 24a5cebf101180822198806c0a4131b0efb7a36d | [
"MIT"
] | null | null | null | python/test/test_tree_dp.py | EQt/treelas | 24a5cebf101180822198806c0a4131b0efb7a36d | [
"MIT"
] | null | null | null | import numpy as np
from treelas import post_order, TreeInstance
def test_demo_3x7_postord():
parent = np.array([0, 4, 5, 0, 3, 4, 7, 8, 5, 6, 7, 8,
9, 14, 17, 12, 15, 16, 19, 16, 17])
po = post_order(parent, include_root=True)
expect = np.array([12, 11, 19, 20, 21, 14, 15, 18, 17, 1... | 37.62069 | 70 | 0.508708 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 114 | 0.104491 |
4ad0334044a6b76510a6250d8488d1fea4817857 | 326 | py | Python | lista01/rpc/ex01_cl.py | SD-CC-UFG/leonardo.fleury | 0a8dfc5752c739f5ff98890477355df8960ad730 | [
"MIT"
] | null | null | null | lista01/rpc/ex01_cl.py | SD-CC-UFG/leonardo.fleury | 0a8dfc5752c739f5ff98890477355df8960ad730 | [
"MIT"
] | null | null | null | lista01/rpc/ex01_cl.py | SD-CC-UFG/leonardo.fleury | 0a8dfc5752c739f5ff98890477355df8960ad730 | [
"MIT"
] | null | null | null | import xmlrpc.client
def main():
s = xmlrpc.client.ServerProxy('http://localhost:9991')
nome = input("Nome: ")
cargo = input("Cargo (programador, operador): ")
salario = float(input("Salário: "))
print("\n\n{}".format(s.atualiza_salario(nome, cargo, salario)))
if __name__ == '__main__':
m... | 20.375 | 68 | 0.628834 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 94 | 0.287462 |
4ad04912e975ba67417ff28c203441d4697e2178 | 846 | py | Python | autocomplete/migrations/0001_initial.py | openshift-eng/art-dashboard-server | af4e78b3d2213c30038cf69de646f25fd57c9e3c | [
"Apache-2.0"
] | 1 | 2020-09-21T06:48:47.000Z | 2020-09-21T06:48:47.000Z | autocomplete/migrations/0001_initial.py | adarshtri/build_interface_server | af4e78b3d2213c30038cf69de646f25fd57c9e3c | [
"Apache-2.0"
] | 5 | 2021-02-05T19:43:08.000Z | 2021-06-04T23:23:29.000Z | autocomplete/migrations/0001_initial.py | openshift-eng/art-dashboard-server | af4e78b3d2213c30038cf69de646f25fd57c9e3c | [
"Apache-2.0"
] | 6 | 2021-02-06T07:21:37.000Z | 2021-06-07T12:40:37.000Z | # Generated by Django 3.0.7 on 2020-07-27 19:23
import build.models
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='AutoCompleteRecord',
fields=[
... | 29.172414 | 100 | 0.588652 | 733 | 0.86643 | 0 | 0 | 0 | 0 | 0 | 0 | 167 | 0.1974 |
4ad19826ee08450eee4ee8d57542ce3dfd0b5399 | 636 | py | Python | unet3d/config.py | fcollman/pytorch-3dunet | 303336bfdc0234f075c70e0c59759d09bc4081b8 | [
"MIT"
] | null | null | null | unet3d/config.py | fcollman/pytorch-3dunet | 303336bfdc0234f075c70e0c59759d09bc4081b8 | [
"MIT"
] | null | null | null | unet3d/config.py | fcollman/pytorch-3dunet | 303336bfdc0234f075c70e0c59759d09bc4081b8 | [
"MIT"
] | null | null | null | import argparse
import os
import torch
import yaml
DEFAULT_DEVICE = 'cuda:0'
def load_config():
parser = argparse.ArgumentParser(description='UNet3D training')
parser.add_argument('--config', type=str, help='Path to the YAML config file', required=True)
args = parser.parse_args()
config = _load_conf... | 26.5 | 97 | 0.720126 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 115 | 0.180818 |
4ad2b9e71e54721776c8640bd3dfe9980a8f4ea4 | 654 | py | Python | src/graph_transpiler/webdnn/backend/webgl/optimize_rules/simplify_channel_mode_conversion/simplify_channel_mode_conversion.py | gunpowder78/webdnn | c659ea49007f91d178ce422a1eebe289516a71ee | [
"MIT"
] | 1 | 2018-07-26T13:52:21.000Z | 2018-07-26T13:52:21.000Z | src/graph_transpiler/webdnn/backend/webgl/optimize_rules/simplify_channel_mode_conversion/simplify_channel_mode_conversion.py | gunpowder78/webdnn | c659ea49007f91d178ce422a1eebe289516a71ee | [
"MIT"
] | null | null | null | src/graph_transpiler/webdnn/backend/webgl/optimize_rules/simplify_channel_mode_conversion/simplify_channel_mode_conversion.py | gunpowder78/webdnn | c659ea49007f91d178ce422a1eebe289516a71ee | [
"MIT"
] | null | null | null | from webdnn.backend.webgl.optimize_rules.simplify_channel_mode_conversion.simplify_nonsense_channel_mode_conversion import \
SimplifyNonsenseChannelModeConversion
from webdnn.backend.webgl.optimize_rules.simplify_channel_mode_conversion.simplify_redundant_channel_mode_conversion import \
SimplifyRedundantChanne... | 46.714286 | 125 | 0.831804 | 258 | 0.394495 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
4ad2c65a15fe6f6a8837baee7e607c55330b95b9 | 3,998 | py | Python | script.video.F4mProxy/lib/flvlib/constants.py | akuala/REPO.KUALA | ea9a157025530d2ce8fa0d88431c46c5352e89d4 | [
"Apache-2.0"
] | 105 | 2015-11-28T00:03:11.000Z | 2021-05-05T20:47:42.000Z | script.video.F4mProxy/lib/flvlib/constants.py | akuala/REPO.KUALA | ea9a157025530d2ce8fa0d88431c46c5352e89d4 | [
"Apache-2.0"
] | 918 | 2015-11-28T14:12:40.000Z | 2022-03-23T20:24:49.000Z | script.video.F4mProxy/lib/flvlib/constants.py | akuala/REPO.KUALA | ea9a157025530d2ce8fa0d88431c46c5352e89d4 | [
"Apache-2.0"
] | 111 | 2015-12-01T14:06:10.000Z | 2020-08-01T10:44:39.000Z | """
The constants used in FLV files and their meanings.
"""
# Tag type
(TAG_TYPE_AUDIO, TAG_TYPE_VIDEO, TAG_TYPE_SCRIPT) = (8, 9, 18)
# Sound format
(SOUND_FORMAT_PCM_PLATFORM_ENDIAN,
SOUND_FORMAT_ADPCM,
SOUND_FORMAT_MP3,
SOUND_FORMAT_PCM_LITTLE_ENDIAN,
SOUND_FORMAT_NELLYMOSER_16KHZ,
SOUND_FORMAT_NELLYMOSER_8KH... | 24.679012 | 68 | 0.765883 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 867 | 0.216858 |
4ad2ee44fa3231c3be7b4de5ecea4010665c6467 | 738 | py | Python | A2/semcor_chunk.py | Rogerwlk/Natural-Language-Processing | e1c0499180cec49ac0060aad7f0da00b61cfac94 | [
"MIT"
] | null | null | null | A2/semcor_chunk.py | Rogerwlk/Natural-Language-Processing | e1c0499180cec49ac0060aad7f0da00b61cfac94 | [
"MIT"
] | null | null | null | A2/semcor_chunk.py | Rogerwlk/Natural-Language-Processing | e1c0499180cec49ac0060aad7f0da00b61cfac94 | [
"MIT"
] | null | null | null | from nltk.corpus import semcor
class semcor_chunk:
def __init__(self, chunk):
self.chunk = chunk
#returns the synset if applicable, otherwise returns None
def get_syn_set(self):
try:
synset = self.chunk.label().synset()
return synset
except AttributeError:
try:
synset = wn.synset(self.chunk.lab... | 19.945946 | 58 | 0.682927 | 487 | 0.659892 | 0 | 0 | 0 | 0 | 0 | 0 | 304 | 0.411924 |
4ad2ef7203bc120919170c5085d9fe1547885b6b | 8,318 | py | Python | gnn_model.py | thoang3/graph_neural_network_benchmark | 72dc031ed23c6684c43d6f2ace03425f9b69cee6 | [
"MIT"
] | null | null | null | gnn_model.py | thoang3/graph_neural_network_benchmark | 72dc031ed23c6684c43d6f2ace03425f9b69cee6 | [
"MIT"
] | null | null | null | gnn_model.py | thoang3/graph_neural_network_benchmark | 72dc031ed23c6684c43d6f2ace03425f9b69cee6 | [
"MIT"
] | null | null | null | import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
from load_cora import load_cora
from baseline_model import create_ffn
from utils import run_experiment
from utils import display_learning_curves
# Graph convolution layer
class GraphConvLayer(layers.Layer):
def __init__(
... | 33.007937 | 103 | 0.709425 | 6,330 | 0.761 | 0 | 0 | 0 | 0 | 0 | 0 | 2,256 | 0.271219 |
4ad31bb3fb3f281f7ca24b5d13a95985f1d2e610 | 868 | py | Python | deps/lib/python3.5/site-packages/netdisco/discoverables/samsung_tv.py | jfarmer08/hassio | 792a6071a97bb33857c14c9937946233c620035c | [
"MIT"
] | 78 | 2017-08-19T03:46:13.000Z | 2020-02-19T04:29:45.000Z | deps/lib/python3.5/site-packages/netdisco/discoverables/samsung_tv.py | jfarmer08/hassio | 792a6071a97bb33857c14c9937946233c620035c | [
"MIT"
] | 5 | 2017-08-21T16:33:08.000Z | 2018-06-21T18:37:18.000Z | deps/lib/python3.5/site-packages/netdisco/discoverables/samsung_tv.py | jfarmer08/hassio | 792a6071a97bb33857c14c9937946233c620035c | [
"MIT"
] | 13 | 2017-08-19T16:46:08.000Z | 2018-11-05T23:11:34.000Z | """Discover Samsung Smart TV services."""
from . import SSDPDiscoverable
from ..const import ATTR_NAME
# For some models, Samsung forces a [TV] prefix to the user-specified name.
FORCED_NAME_PREFIX = '[TV]'
class Discoverable(SSDPDiscoverable):
"""Add support for discovering Samsung Smart TV services."""
de... | 33.384615 | 79 | 0.691244 | 657 | 0.756912 | 0 | 0 | 0 | 0 | 0 | 0 | 390 | 0.449309 |
4ad35edb76ff8aacbd63002439bbf9d2f5995fd2 | 59 | py | Python | pyecsca/sca/re/__init__.py | scrambler-crypto/pyecsca | 491abfb548455669abd470382a48dcd07b2eda87 | [
"MIT"
] | 24 | 2019-07-01T00:27:24.000Z | 2022-02-17T00:46:28.000Z | pyecsca/sca/re/__init__.py | scrambler-crypto/pyecsca | 491abfb548455669abd470382a48dcd07b2eda87 | [
"MIT"
] | 18 | 2020-12-10T15:08:56.000Z | 2022-03-01T11:44:37.000Z | pyecsca/sca/re/__init__.py | scrambler-crypto/pyecsca | 491abfb548455669abd470382a48dcd07b2eda87 | [
"MIT"
] | 7 | 2020-02-20T18:44:29.000Z | 2021-11-30T21:16:44.000Z | """Package for reverse-engineering."""
from .rpa import *
| 14.75 | 38 | 0.694915 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 38 | 0.644068 |
4ad38b4a5080c2f9ece1062934512164a3b8e38a | 324 | py | Python | sapmi/employees/migrations/0002_remove_employee_phone_alt.py | Juhanostby/django-apotek-sapmi | 972a05ca9d54eed62b640572fcf582cc8751d15a | [
"MIT"
] | 1 | 2021-09-04T17:29:14.000Z | 2021-09-04T17:29:14.000Z | sapmi/employees/migrations/0002_remove_employee_phone_alt.py | Juhanostby/django-apotek-sapmi | 972a05ca9d54eed62b640572fcf582cc8751d15a | [
"MIT"
] | 1 | 2021-07-19T15:54:27.000Z | 2021-07-20T23:01:57.000Z | sapmi/employees/migrations/0002_remove_employee_phone_alt.py | Juhanostby/django-apotek-sapmi | 972a05ca9d54eed62b640572fcf582cc8751d15a | [
"MIT"
] | null | null | null | # Generated by Django 3.2.5 on 2021-12-21 19:42
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('employees', '0001_initial'),
]
operations = [
migrations.RemoveField(
model_name='employee',
name='phone_alt',
),
... | 18 | 47 | 0.58642 | 239 | 0.737654 | 0 | 0 | 0 | 0 | 0 | 0 | 93 | 0.287037 |
4ad430bf0f736b3775616810d3e0ff10960723c4 | 124 | py | Python | src/model/exception/emote_fetch_error.py | konrad2508/kokomi-discord-bot | 5a9d459e92d552fa24ba3ada5188db19d93f0aaa | [
"MIT"
] | 2 | 2022-03-02T15:56:41.000Z | 2022-03-10T16:30:41.000Z | src/model/exception/emote_fetch_error.py | konrad2508/kokomi-discord-bot | 5a9d459e92d552fa24ba3ada5188db19d93f0aaa | [
"MIT"
] | 2 | 2022-03-10T16:30:20.000Z | 2022-03-16T14:33:59.000Z | src/model/exception/emote_fetch_error.py | konrad2508/kokomi-discord-bot | 5a9d459e92d552fa24ba3ada5188db19d93f0aaa | [
"MIT"
] | null | null | null | class EmoteFetchError(Exception):
'''Exception stating that there was a problem while fetching emotes from a source.'''
| 41.333333 | 89 | 0.766129 | 123 | 0.991935 | 0 | 0 | 0 | 0 | 0 | 0 | 85 | 0.685484 |
4ad45250872794a6a29b08c6da2bcb27a740d5f5 | 5,098 | py | Python | src/sim/basicExample/main.py | andremtsilva/dissertacao | 7c039ffe871468be0215c482adb42830fff586aa | [
"MIT"
] | null | null | null | src/sim/basicExample/main.py | andremtsilva/dissertacao | 7c039ffe871468be0215c482adb42830fff586aa | [
"MIT"
] | null | null | null | src/sim/basicExample/main.py | andremtsilva/dissertacao | 7c039ffe871468be0215c482adb42830fff586aa | [
"MIT"
] | null | null | null | """
This is the most simple scenario with a basic topology, some users and a set of apps with only one service.
@author: Isaac Lera
"""
import os
import time
import json
import random
import logging.config
import networkx as nx
import numpy as np
from pathlib import Path
from yafs.core import Sim
from yafs.a... | 27.857923 | 156 | 0.652217 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2,097 | 0.411338 |
4ad523fc14942dd490ad41c526c6171f60967ac3 | 476 | py | Python | Backend/models/risklayerPrognosis.py | dbvis-ukon/coronavis | f00374ac655c9d68541183d28ede6fe5536581dc | [
"Apache-2.0"
] | 15 | 2020-04-24T20:18:11.000Z | 2022-01-31T21:05:05.000Z | Backend/models/risklayerPrognosis.py | dbvis-ukon/coronavis | f00374ac655c9d68541183d28ede6fe5536581dc | [
"Apache-2.0"
] | 2 | 2021-05-19T07:15:09.000Z | 2022-03-07T08:29:34.000Z | Backend/models/risklayerPrognosis.py | dbvis-ukon/coronavis | f00374ac655c9d68541183d28ede6fe5536581dc | [
"Apache-2.0"
] | 4 | 2020-04-27T16:20:13.000Z | 2021-02-23T10:39:42.000Z | from db import db
class RisklayerPrognosis(db.Model):
__tablename__ = 'risklayer_prognosis'
datenbestand = db.Column(db.TIMESTAMP, primary_key=True, nullable=False)
prognosis = db.Column(db.Float, nullable=False)
# class RisklayerPrognosisSchema(SQLAlchemyAutoSchema):
# class Meta:
# strict ... | 28 | 76 | 0.72479 | 207 | 0.434874 | 0 | 0 | 0 | 0 | 0 | 0 | 261 | 0.548319 |
4ad5abaadbbca74176e6ec4d71b60fea9789204e | 2,520 | py | Python | tests.py | smartfile/django-secureform | 3b7a8b90550327f370ea02c6886220b2db0517b5 | [
"MIT"
] | 12 | 2015-02-23T19:45:45.000Z | 2021-05-05T20:35:26.000Z | tests.py | smartfile/django-secureform | 3b7a8b90550327f370ea02c6886220b2db0517b5 | [
"MIT"
] | 3 | 2015-08-09T18:14:16.000Z | 2018-10-23T03:16:38.000Z | tests.py | smartfile/django-secureform | 3b7a8b90550327f370ea02c6886220b2db0517b5 | [
"MIT"
] | 6 | 2015-05-09T07:46:00.000Z | 2019-11-27T09:54:57.000Z | import os
import unittest
os.environ['DJANGO_SETTINGS_MODULE'] = 'settings'
import django
if django.VERSION >= (1, 7):
django.setup()
from django import forms
from django.db import models
from django.forms.forms import NON_FIELD_ERRORS
from django_secureform.forms import SecureForm
def get_form_sname(form, name... | 28.965517 | 94 | 0.660714 | 1,675 | 0.664683 | 0 | 0 | 0 | 0 | 0 | 0 | 256 | 0.101587 |
4ad5badf5fa7e630a25fb87b42b8e063138bfecd | 495 | py | Python | opencv/resizing.py | hackerman-101/Hacktoberfest-2022 | 839f28293930987da55f8a2414efaa1cf9676cc9 | [
"MIT"
] | 1 | 2022-02-22T17:13:54.000Z | 2022-02-22T17:13:54.000Z | opencv/resizing.py | hackerman-101/Hacktoberfest-2022 | 839f28293930987da55f8a2414efaa1cf9676cc9 | [
"MIT"
] | 11 | 2022-01-24T20:42:11.000Z | 2022-02-27T23:58:24.000Z | opencv/resizing.py | hackerman-101/Hacktoberfest-2022 | 839f28293930987da55f8a2414efaa1cf9676cc9 | [
"MIT"
] | null | null | null | import cv2 as cv
import numpy as np
cap = cv.VideoCapture(1)
print(cap.get(cv.CAP_PROP_FRAME_WIDTH))
print(cap.get(cv.CAP_PROP_FRAME_HEIGHT))
cap.set(3,3000)
cap.set(4,3000)
print(cap.get(cv.CAP_PROP_FRAME_WIDTH))
print(cap.get(cv.CAP_PROP_FRAME_HEIGHT))
while (cap.isOpened()):
ret , frame = cap.read()
if... | 18.333333 | 45 | 0.656566 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 0.022222 |