Reset23/the-stack-v2-filtered-python · Datasets at Hugging Face

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#!/usr/bin/env python3 from reporter.connections import RedcapInstance from reporter.application_abstract_reports.redcap.percentage_complete import ( RedcapPercentageCompleteReport, ) from reporter.application_abstract_reports.redcap.withdrawn_or_excluded_with_data import ( RedcapWithdrawnOrExcludedWithDataReport, ) from reporter.emailing import ( RECIPIENT_LENTEN_ADMIN as RECIPIENT_ADMIN, RECIPIENT_LENTEN_MANAGER as RECIPIENT_MANAGER, RECIPIENT_IT_DQ, ) from reporter.application_abstract_reports.redcap.web_data_quality import ( RedcapWebDataQuality, ) from reporter.core import Schedule REDCAP_PROJECT_ID = 25 REDCAP_INSTANCE = RedcapInstance.internal class LentenRedcapPercentageCompleteReport(RedcapPercentageCompleteReport): def __init__(self): super().__init__( 'Lenten', [RECIPIENT_ADMIN, RECIPIENT_MANAGER], ) class LentenRedcapWithdrawnOrExcludedWithDataReport( RedcapWithdrawnOrExcludedWithDataReport): def __init__(self): super().__init__( 'Lenten', [RECIPIENT_ADMIN, RECIPIENT_MANAGER], schedule=Schedule.never, ) class LentenRedcapWebDataQuality(RedcapWebDataQuality): def __init__(self): super().__init__( REDCAP_INSTANCE, REDCAP_PROJECT_ID, [RECIPIENT_IT_DQ] )

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""" WSGI config for AuthDemo project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/2.1/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'AuthDemo.settings') application = get_wsgi_application()

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# Embedded file name: scripts/client/gui/Scaleform/daapi/view/dialogs/SystemMessageDialog.py from gui.Scaleform.daapi.view.meta.SystemMessageDialogMeta import SystemMessageDialogMeta class SystemMessageDialog(SystemMessageDialogMeta): def __init__(self, meta, handler): super(SystemMessageDialog, self).__init__() self.__meta = meta self.__handler = handler def _populate(self): super(SystemMessageDialog, self)._populate() self.as_setInitDataS({'title': self.__meta.getTitle(), 'closeBtnTitle': self.__meta.getCancelLabel(), 'settings': self.__meta.getSettings()}) self.as_setMessageDataS(self.__meta.getMessageObject()) def onWindowClose(self): self.destroy() def _dispose(self): if self.__handler: self.__handler(True) self.__meta.cleanUp() self.__meta = None self.__handler = None super(SystemMessageDialog, self)._dispose() return

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import pygame import sys SCREEN_WIDTH = 2560 SCREEN_HEIGHT = 1440 white = (255, 255, 255) black = (0, 0, 0) pygame.init() pygame.display.set_caption("Dokdo Defense") #screen = pygame.display.set_mode((2560, 1440), pygame.FULLSCREEN) screen = pygame.display.set_mode((SCREEN_WIDTH, SCREEN_HEIGHT)) def startScreen(screen): background = pygame.Rect((0,0), (SCREEN_WIDTH, SCREEN_HEIGHT)) pygame.draw.rect(screen, white, background) cardimg=pygame.image.load('res/back_1.png') clock = pygame.time.Clock() while True: clock.tick(10) for event in pygame.event.get(): if event.type == pygame.QUIT: sys.exit() if event.type == pygame.KEYDOWN: if event.key == pygame.K_q: sys.exit() start() pygame.quit()

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class Solution(object): def fizzBuzz(self, n): """ :type n: int :rtype: List[str] """ res = [] for i in range(1, n + 1): if not i % 3 and not i % 5: res.append('FizzBuzz') continue if not i % 3: res.append('Fizz') continue if not i % 5: res.append('Buzz') continue res.append(str(i)) return res

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from django.contrib import admin from .models import Category,Product # Register your models here. class CategoryAdmin(admin.ModelAdmin): list_display = ['name', 'slug'] prepopulated_fields = {'slug': ('name',)} class ProductAdmin(admin.ModelAdmin): list_display = ['name', 'slug', 'category', 'price', 'stock', 'available', 'created', 'updated'] list_filter = ['available', 'created', 'updated', 'category'] list_editable = ['price', 'stock', 'available'] prepopulated_fields = {'slug': ('name',)} admin.site.register(Category, CategoryAdmin) admin.site.register(Product, ProductAdmin)

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from django.db import models from django.db.models.constraints import UniqueConstraint from django.core.exceptions import ValidationError from datetime import date from users.models import Cicle # Create your models here. #Modelos que se van a migrar a la base de datos y que sirven para formae los elementos de la web #################Validators############## def validate_date(value): actualdate=date.today() if(actualdate>value): raise ValidationError( "La fecha del evento tiene que ser posterior a la actual" ) ######################################### #MODELO DE EVENTOS class Event(models.Model): id=models.AutoField(primary_key=True) date=models.DateField(blank=False,null=False,validators=[validate_date]) Description=models.CharField(max_length=400) created_at=models.DateField(auto_now_add=True) updated_at=models.DateField(auto_now=True) class Meta: db_table="events" ordering= ["date"] #SELECCION DE # #MODELO DE HORARIOS class Timetable(models.Model): id=models.AutoField(primary_key=True) cicle = models.OneToOneField(Cicle, on_delete=models.CASCADE,unique=True) timetable_image=models.ImageField(upload_to="timetables") timetable_created_at=models.DateField(auto_now_add=True) timetable_updated_at=models.DateField(auto_now=True) created_at=models.DateField(auto_now_add=True) updated_at=models.DateField(auto_now=True) class Meta: db_table="timetables" #MODELO DE MENUS class Menu(models.Model): id=models.AutoField(primary_key=True) cicle = models.OneToOneField(Cicle, on_delete=models.CASCADE,unique=True) menu_image=models.ImageField(upload_to="menus") created_at=models.DateField(auto_now_add=True) updated_at=models.DateField(auto_now=True) class Meta: db_table="menus" class New(models.Model): id=models.AutoField(primary_key=True) #Id autoincremental title=models.CharField(max_length=50) subtitle=models.CharField(max_length=100) content=models.TextField(max_length=3000) media1=models.ImageField(upload_to="news") #Estas imágenes no son obligatorias, solo lo es una para el encabezado de la noticia media2=models.ImageField(blank=True, null=True) media3=models.ImageField(blank=True, null=True) media4=models.ImageField(blank=True, null=True) media5=models.ImageField(blank=True, null=True) media6=models.ImageField(blank=True, null=True) created_at=models.DateField(auto_now_add=True) updated_at=models.DateField(auto_now=True) class Meta: db_table="news"

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import os from yggdrasil.examples.tests import TestExample class TestExampleFIO9(TestExample): r"""Test the Formatted I/O lesson 9 example.""" example_name = 'formatted_io9' @property def input_files(self): r"""Input file.""" return [os.path.join(self.yamldir, 'Input', 'input.txt')] @property def output_files(self): r"""Output file.""" return [os.path.join(self.yamldir, 'output.txt')]

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import os import sys import setuptools try: import builtins except ImportError: import __builtin__ as builtins PATH_ROOT = PATH_ROOT = os.path.dirname(__file__) builtins.__LIGHTLY_SETUP__ = True import lightly def load_description(path_dir=PATH_ROOT, filename="DOCS.md"): """Load long description from readme in the path_dir/ directory""" with open(os.path.join(path_dir, filename)) as f: long_description = f.read() return long_description def load_requirements(path_dir=PATH_ROOT, filename="base.txt", comment_char="#"): """From pytorch-lightning repo: https://github.com/PyTorchLightning/pytorch-lightning. Load requirements from text file in the path_dir/requirements/ directory. """ with open(os.path.join(path_dir, "requirements", filename), "r") as file: lines = [ln.strip() for ln in file.readlines()] reqs = [] for ln in lines: # filer all comments if comment_char in ln: ln = ln[: ln.index(comment_char)].strip() # skip directly installed dependencies if ln.startswith("http"): continue if ln: # if requirement is not empty reqs.append(ln) return reqs if __name__ == "__main__": name = "lightly" version = lightly.__version__ description = lightly.__doc__ author = "Philipp Wirth & Igor Susmelj" author_email = "philipp@lightly.ai" description = "A deep learning package for self-supervised learning" entry_points = { "console_scripts": [ "lightly-crop = lightly.cli.crop_cli:entry", "lightly-train = lightly.cli.train_cli:entry", "lightly-embed = lightly.cli.embed_cli:entry", "lightly-magic = lightly.cli.lightly_cli:entry", "lightly-download = lightly.cli.download_cli:entry", "lightly-version = lightly.cli.version_cli:entry", ] } long_description = load_description() python_requires = ">=3.6" base_requires = load_requirements(filename="base.txt") openapi_requires = load_requirements(filename="openapi.txt") torch_requires = load_requirements(filename="torch.txt") video_requires = load_requirements(filename="video.txt") dev_requires = load_requirements(filename="dev.txt") setup_requires = ["setuptools>=21"] install_requires = base_requires + openapi_requires + torch_requires extras_require = { "video": video_requires, "dev": dev_requires, "all": dev_requires + video_requires, } packages = [ "lightly", "lightly.api", "lightly.cli", "lightly.cli.config", "lightly.data", "lightly.embedding", "lightly.loss", "lightly.loss.regularizer", "lightly.models", "lightly.models.modules", "lightly.transforms", "lightly.utils", "lightly.utils.benchmarking", "lightly.utils.cropping", "lightly.active_learning", "lightly.active_learning.config", "lightly.openapi_generated", "lightly.openapi_generated.swagger_client", "lightly.openapi_generated.swagger_client.api", "lightly.openapi_generated.swagger_client.models", ] project_urls = { "Homepage": "https://www.lightly.ai", "Web-App": "https://app.lightly.ai", "Documentation": "https://docs.lightly.ai", "Github": "https://github.com/lightly-ai/lightly", "Discord": "https://discord.gg/xvNJW94", } classifiers = [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "Intended Audience :: Education", "Intended Audience :: Science/Research", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Mathematics", "Topic :: Scientific/Engineering :: Artificial Intelligence", "Topic :: Software Development", "Topic :: Software Development :: Libraries", "Topic :: Software Development :: Libraries :: Python Modules", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "License :: OSI Approved :: MIT License", ] setuptools.setup( name=name, version=version, author=author, author_email=author_email, description=description, entry_points=entry_points, license="MIT", long_description=long_description, long_description_content_type="text/markdown", setup_requires=setup_requires, install_requires=install_requires, extras_require=extras_require, python_requires=python_requires, packages=packages, classifiers=classifiers, include_package_data=True, project_urls=project_urls, )

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""" Django settings for myproject project. Generated by 'django-admin startproject' using Django 3.0.8. For more information on this file, see https://docs.djangoproject.com/en/3.0/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/3.0/ref/settings/ """ import os # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/3.0/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'luc4h*=^mfhxz!8kc*5aprn6b#nou=*7$9e(uy_-vquj%ln&f2' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = [] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'myapp' ] MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'myproject.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [os.path.join(BASE_DIR, 'myapp', 'templates')], #updated 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'myproject.wsgi.application' # Database # https://docs.djangoproject.com/en/3.0/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/3.0/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/3.0/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/3.0/howto/static-files/ STATIC_URL = '/static/' LOGIN_URL = '/login/' LOGIN_REDIRECT_URL = '/secure'

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# Copyright 2009 10gen, 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 agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Tests for the dbref module.""" import unittest import types import sys sys.path[0:0] = [""] from pymongo.objectid import ObjectId from pymongo.dbref import DBRef class TestDBRef(unittest.TestCase): def setUp(self): pass def test_creation(self): a = ObjectId() self.assertRaises(TypeError, DBRef) self.assertRaises(TypeError, DBRef, "coll") self.assertRaises(TypeError, DBRef, 4, a) self.assertRaises(TypeError, DBRef, 1.5, a) self.assertRaises(TypeError, DBRef, a, a) self.assertRaises(TypeError, DBRef, None, a) self.assert_(DBRef("coll", a)) self.assert_(DBRef(u"coll", a)) self.assert_(DBRef(u"coll", 5)) def test_read_only(self): a = DBRef("coll", ObjectId()) def foo(): a.collection = "blah" def bar(): a.id = "aoeu" a.collection a.id self.assertRaises(AttributeError, foo) self.assertRaises(AttributeError, bar) def test_repr(self): self.assertEqual(repr(DBRef("coll", ObjectId("123456789012"))), "DBRef(u'coll', ObjectId('123456789012'))") self.assertEqual(repr(DBRef(u"coll", ObjectId("123456789012"))), "DBRef(u'coll', ObjectId('123456789012'))") def test_cmp(self): self.assertEqual(DBRef("coll", ObjectId("123456789012")), DBRef(u"coll", ObjectId("123456789012"))) self.assertNotEqual(DBRef("coll", ObjectId("123456789012")), DBRef("col", ObjectId("123456789012"))) self.assertNotEqual(DBRef("coll", ObjectId("123456789012")), DBRef("coll", ObjectId("123456789011"))) self.assertNotEqual(DBRef("coll", ObjectId("123456789012")), 4) if __name__ == "__main__": unittest.main()

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"""servicequotas module initialization; sets value for base decorator.""" from .models import servicequotas_backends from ..core.models import base_decorator mock_servicequotas = base_decorator(servicequotas_backends)

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a4513dc5f798434e87c43e29f84c7060515b1e12

[]

no_license

PeterMitrano/my_cookbook

dd8b91170cd101d453c942972a87b2d85dc163b4

46d47e863d10947b3052fc59351da5d83a8dba36

refs/heads/master

2021-01-19T06:36:26.718989

2016-10-17T03:35:17

61,961,054

0

null

UTF-8

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import copy import json import logging import os from my_cookbook import stage from my_cookbook.skill import intent_handler from my_cookbook.util import responder from my_cookbook.util import core from my_cookbook.util import dbhelper import my_cookbook.skill.handlers as handlers import pkgutil class Skill: def __init__(self): self.intent_handler = intent_handler.Handler() # automagically add all the handlers for importer, modname, _ in pkgutil.iter_modules(handlers.__path__): handler_mod = importer.find_module(modname).load_module(modname) self.intent_handler.add(handler_mod.state, handler_mod.handler) def handle_event(self, event, context): # check if we're debugging locally if stage.PROD: debug = False endpoint_url = None logging.getLogger(core.LOGGER).setLevel(logging.INFO) else: debug = True logging.getLogger(core.LOGGER).setLevel(logging.DEBUG) endpoint_url = core.LOCAL_DB_URI # check application id and user user = event['session']['user']['userId'] request_appId = event['session']['application']['applicationId'] if core.APP_ID != request_appId: raise Exception('application id %s does not match.' % request_appId) # store session attributes so the various handlers know what's up if 'attributes' in event['session']: session_attributes = event['session']['attributes'] else: session_attributes = {} # try to pull the current values from the database so we can initialize # the persistant_attributes dict. This will also create the user if they # do not exist self.db_helper = dbhelper.DBHelper(user, endpoint_url) self.db_helper.init_table() result = self.db_helper.getAll() persistant_attributes = {} if result.value: #user at least exists persistant_attributes = result.value # but we don't want to save the userId so pop that persistant_attributes.pop('userId', None) initial_persistant_attributes = copy.deepcopy(persistant_attributes) # next try to figure out the current state. Look in the event first # and if that fails check our database via the persistant_attributes we just got state = "" if core.STATE_KEY in session_attributes: state = session_attributes[core.STATE_KEY] elif core.STATE_KEY in persistant_attributes: state = persistant_attributes[core.STATE_KEY] # increment invocations if this is a new session. invocations is used # to improve VUI because we know how many times the user has used the skill if event['session']['new']: if 'invocations' in persistant_attributes: persistant_attributes['invocations'] += 1 else: persistant_attributes['invocations'] = 1 # add whether the request is 'new' into the attributes for conveneince # and make sure state is in session_attributes, not persistant attributes session_attributes['new'] = event['session']['new'] session_attributes['user'] = user # at this point we either know the state, or we have returned an error, # or we know it's the users first time and there is no state # so now we dispatch response = self.intent_handler.dispatch(state, persistant_attributes, session_attributes, event) # now that we're done, we need to favorite the recipe # the persistant_attributes dict to our database # but only do it if something change if persistant_attributes != initial_persistant_attributes: self.db_helper.setAll(persistant_attributes) # don't delete this or you can't debug production logging.getLogger(core.LOGGER).warn(json.dumps(response, indent=2)) # ok we're finally done return response

[ "mitranopeter@gmail.com" ]

mitranopeter@gmail.com

b45f60440404180a0a7bd6b2360db7563ad17d57

6946c6ff6fa229e5b968928b34620fe85192729b

/val/evaluate_atr.py

98169caa00056c9cb0bdb0597d90690d67ec181f

[]

no_license

wovai/Hierarchical-Human-Parsing

8a98236930b239fb412033b67c2614376e42769a

58737dbb7763f5a7baafd4801c5a287facf536cd

refs/heads/master

2022-12-18T12:53:10.928088

2020-09-19T15:26:17

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UTF-8

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py

import argparse import os import cv2 import matplotlib.pyplot as plt import numpy as np import torch import torch.nn as nn from torch.autograd import Variable from torch.utils import data from dataset.data_atr import ATRTestGenerator as TestGenerator from network.baseline import get_model def get_arguments(): """Parse all the arguments provided from the CLI. Returns: A list of parsed arguments. """ parser = argparse.ArgumentParser(description="Pytorch Segmentation") parser.add_argument("--root", type=str, default='./data/ATR/test_set/') parser.add_argument("--data-list", type=str, default='./dataset/ATR/test_id.txt') parser.add_argument("--crop-size", type=int, default=513) parser.add_argument("--num-classes", type=int, default=18) parser.add_argument("--ignore-label", type=int, default=255) parser.add_argument("--restore-from", type=str, default='./checkpoints/exp/model_best.pth') parser.add_argument("--is-mirror", action="store_true") parser.add_argument('--eval-scale', nargs='+', type=float, default=[1.0]) # parser.add_argument('--eval-scale', nargs='+', type=float, default=[0.50, 0.75, 1.0, 1.25, 1.50, 1.75]) parser.add_argument("--save-dir", type=str) parser.add_argument("--gpu", type=str, default='0') return parser.parse_args() def main(): """Create the model and start the evaluation process.""" args = get_arguments() # initialization print("Input arguments:") for key, val in vars(args).items(): print("{:16} {}".format(key, val)) os.environ["CUDA_VISIBLE_DEVICES"] = args.gpu model = get_model(num_classes=args.num_classes) # if not os.path.exists(args.save_dir): # os.makedirs(args.save_dir) palette = get_lip_palette() restore_from = args.restore_from saved_state_dict = torch.load(restore_from) model.load_state_dict(saved_state_dict) model.eval() model.cuda() testloader = data.DataLoader(TestGenerator(args.root, args.data_list, crop_size=args.crop_size), batch_size=1, shuffle=False, pin_memory=True) confusion_matrix = np.zeros((args.num_classes, args.num_classes)) for index, batch in enumerate(testloader): if index % 100 == 0: print('%d images have been proceeded' % index) image, label, ori_size, name = batch ori_size = ori_size[0].numpy() output = predict(model, image.numpy(), (np.asscalar(ori_size[0]), np.asscalar(ori_size[1])), is_mirror=args.is_mirror, scales=args.eval_scale) seg_pred = np.asarray(np.argmax(output, axis=2), dtype=np.uint8) # output_im = PILImage.fromarray(seg_pred) # output_im.putpalette(palette) # output_im.save(args.save_dir + name[0] + '.png') seg_gt = np.asarray(label[0].numpy(), dtype=np.int) ignore_index = seg_gt != 255 seg_gt = seg_gt[ignore_index] seg_pred = seg_pred[ignore_index] confusion_matrix += get_confusion_matrix(seg_gt, seg_pred, args.num_classes) pos = confusion_matrix.sum(1) res = confusion_matrix.sum(0) tp = np.diag(confusion_matrix) pixel_accuracy = tp.sum() / pos.sum() mean_accuracy = (tp / np.maximum(1.0, pos)).mean() IU_array = (tp / np.maximum(1.0, pos + res - tp)) mean_IU = IU_array.mean() # get_confusion_matrix_plot() print('Pixel accuracy: %f \n' % pixel_accuracy) print('Mean accuracy: %f \n' % mean_accuracy) print('Mean IU: %f \n' % mean_IU) for index, IU in enumerate(IU_array): print('%f ', IU) def scale_image(image, scale): image = image[0, :, :, :] image = image.transpose((1, 2, 0)) image = cv2.resize(image, None, fx=scale, fy=scale, interpolation=cv2.INTER_LINEAR) image = image.transpose((2, 0, 1)) return image def predict(net, image, output_size, is_mirror=True, scales=[1]): if is_mirror: image_rev = image[:, :, :, ::-1] interp = nn.Upsample(size=output_size, mode='bilinear', align_corners=True) outputs = [] if is_mirror: for scale in scales: if scale != 1: image_scale = scale_image(image=image, scale=scale) image_rev_scale = scale_image(image=image_rev, scale=scale) else: image_scale = image[0, :, :, :] image_rev_scale = image_rev[0, :, :, :] image_scale = np.stack((image_scale, image_rev_scale)) with torch.no_grad(): prediction = net(Variable(torch.from_numpy(image_scale)).cuda()) prediction = interp(prediction[0]).cpu().data.numpy() prediction_rev = prediction[1, :, :, :].copy() prediction_rev[9, :, :] = prediction[1, 10, :, :] prediction_rev[10, :, :] = prediction[1, 9, :, :] prediction_rev[12, :, :] = prediction[1, 13, :, :] prediction_rev[13, :, :] = prediction[1, 12, :, :] prediction_rev[14, :, :] = prediction[1, 15, :, :] prediction_rev[15, :, :] = prediction[1, 14, :, :] prediction_rev = prediction_rev[:, :, ::-1] prediction = prediction[0, :, :, :] prediction = np.mean([prediction, prediction_rev], axis=0) outputs.append(prediction) outputs = np.mean(outputs, axis=0) outputs = outputs.transpose(1, 2, 0) else: for scale in scales: if scale != 1: image_scale = scale_image(image=image, scale=scale) else: image_scale = image[0, :, :, :] with torch.no_grad(): prediction = net(Variable(torch.from_numpy(image_scale).unsqueeze(0)).cuda()) prediction = interp(prediction[0]).cpu().data.numpy() outputs.append(prediction[0, :, :, :]) outputs = np.mean(outputs, axis=0) outputs = outputs.transpose(1, 2, 0) return outputs def get_confusion_matrix(gt_label, pred_label, class_num): """ Calculate the confusion matrix by given label and pred :param gt_label: the ground truth label :param pred_label: the pred label :param class_num: the nunber of class """ index = (gt_label * class_num + pred_label).astype('int32') label_count = np.bincount(index) confusion_matrix = np.zeros((class_num, class_num)) for i_label in range(class_num): for i_pred_label in range(class_num): cur_index = i_label * class_num + i_pred_label if cur_index < len(label_count): confusion_matrix[i_label, i_pred_label] = label_count[cur_index] return confusion_matrix def get_confusion_matrix_plot(conf_arr): norm_conf = [] for i in conf_arr: tmp_arr = [] a = sum(i, 0) for j in i: tmp_arr.append(float(j) / max(1.0, float(a))) norm_conf.append(tmp_arr) fig = plt.figure() plt.clf() ax = fig.add_subplot(111) ax.set_aspect(1) res = ax.imshow(np.array(norm_conf), cmap=plt.cm.jet, interpolation='nearest') width, height = conf_arr.shape cb = fig.colorbar(res) alphabet = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' plt.xticks(range(width), alphabet[:width]) plt.yticks(range(height), alphabet[:height]) plt.savefig('confusion_matrix.png', format='png') def get_lip_palette(): palette = [0, 0, 0, 128, 0, 0, 255, 0, 0, 0, 85, 0, 170, 0, 51, 255, 85, 0, 0, 0, 85, 0, 119, 221, 85, 85, 0, 0, 85, 85, 85, 51, 0, 52, 86, 128, 0, 128, 0, 0, 0, 255, 51, 170, 221, 0, 255, 255, 85, 255, 170, 170, 255, 85, 255, 255, 0, 255, 170, 0] return palette if __name__ == '__main__': main()

[ "908865817@qq.com" ]

908865817@qq.com

2e37583a1831659a3dc55f96a8b9ced27ebfee96

c071eb46184635818e8349ce9c2a78d6c6e460fc

/system/python_stubs/-745935208/PySide2/QtNetwork/QNetworkRequest.py

ccb10fdfe22346491df2ee7774c525d73ba453d0

[]

no_license

sidbmw/PyCharm-Settings

a71bc594c83829a1522e215155686381b8ac5c6e

083f9fe945ee5358346e5d86b17130d521d1b954

refs/heads/master

2020-04-05T14:24:03.216082

2018-12-28T02:29:29

156,927,399

0

null

UTF-8

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false

6,151

py

# encoding: utf-8 # module PySide2.QtNetwork # from C:\Users\siddh\AppData\Local\Programs\Python\Python37\lib\site-packages\PySide2\QtNetwork.pyd # by generator 1.146 # no doc # imports import PySide2.QtCore as __PySide2_QtCore import Shiboken as __Shiboken class QNetworkRequest(__Shiboken.Object): # no doc def attribute(self, *args, **kwargs): # real signature unknown pass def hasRawHeader(self, *args, **kwargs): # real signature unknown pass def header(self, *args, **kwargs): # real signature unknown pass def maximumRedirectsAllowed(self, *args, **kwargs): # real signature unknown pass def originatingObject(self, *args, **kwargs): # real signature unknown pass def priority(self, *args, **kwargs): # real signature unknown pass def rawHeader(self, *args, **kwargs): # real signature unknown pass def rawHeaderList(self, *args, **kwargs): # real signature unknown pass def setAttribute(self, *args, **kwargs): # real signature unknown pass def setHeader(self, *args, **kwargs): # real signature unknown pass def setMaximumRedirectsAllowed(self, *args, **kwargs): # real signature unknown pass def setOriginatingObject(self, *args, **kwargs): # real signature unknown pass def setPriority(self, *args, **kwargs): # real signature unknown pass def setRawHeader(self, *args, **kwargs): # real signature unknown pass def setSslConfiguration(self, *args, **kwargs): # real signature unknown pass def setUrl(self, *args, **kwargs): # real signature unknown pass def sslConfiguration(self, *args, **kwargs): # real signature unknown pass def swap(self, *args, **kwargs): # real signature unknown pass def url(self, *args, **kwargs): # real signature unknown pass def __copy__(self, *args, **kwargs): # real signature unknown pass def __eq__(self, *args, **kwargs): # real signature unknown """ Return self==value. """ pass def __ge__(self, *args, **kwargs): # real signature unknown """ Return self>=value. """ pass def __gt__(self, *args, **kwargs): # real signature unknown """ Return self>value. """ pass def __init__(self, *args, **kwargs): # real signature unknown pass def __le__(self, *args, **kwargs): # real signature unknown """ Return self<=value. """ pass def __lt__(self, *args, **kwargs): # real signature unknown """ Return self<value. """ pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __ne__(self, *args, **kwargs): # real signature unknown """ Return self!=value. """ pass AlwaysCache = None # (!) real value is '' AlwaysNetwork = None # (!) real value is '' Attribute = None # (!) real value is '' AuthenticationReuseAttribute = None # (!) real value is '' Automatic = None # (!) real value is '' BackgroundRequestAttribute = None # (!) real value is '' CacheLoadControl = None # (!) real value is '' CacheLoadControlAttribute = None # (!) real value is '' CacheSaveControlAttribute = None # (!) real value is '' ConnectionEncryptedAttribute = None # (!) real value is '' ContentDispositionHeader = None # (!) real value is '' ContentLengthHeader = None # (!) real value is '' ContentTypeHeader = None # (!) real value is '' CookieHeader = None # (!) real value is '' CookieLoadControlAttribute = None # (!) real value is '' CookieSaveControlAttribute = None # (!) real value is '' CustomVerbAttribute = None # (!) real value is '' DoNotBufferUploadDataAttribute = None # (!) real value is '' DownloadBufferAttribute = None # (!) real value is '' EmitAllUploadProgressSignalsAttribute = None # (!) real value is '' FollowRedirectsAttribute = None # (!) real value is '' HighPriority = None # (!) real value is '' HTTP2AllowedAttribute = None # (!) real value is '' Http2DirectAttribute = None # (!) real value is '' HTTP2WasUsedAttribute = None # (!) real value is '' HttpPipeliningAllowedAttribute = None # (!) real value is '' HttpPipeliningWasUsedAttribute = None # (!) real value is '' HttpReasonPhraseAttribute = None # (!) real value is '' HttpStatusCodeAttribute = None # (!) real value is '' KnownHeaders = None # (!) real value is '' LastModifiedHeader = None # (!) real value is '' LoadControl = None # (!) real value is '' LocationHeader = None # (!) real value is '' LowPriority = None # (!) real value is '' Manual = None # (!) real value is '' ManualRedirectPolicy = None # (!) real value is '' MaximumDownloadBufferSizeAttribute = None # (!) real value is '' NoLessSafeRedirectPolicy = None # (!) real value is '' NormalPriority = None # (!) real value is '' OriginalContentLengthAttribute = None # (!) real value is '' PreferCache = None # (!) real value is '' PreferNetwork = None # (!) real value is '' Priority = None # (!) real value is '' RedirectionTargetAttribute = None # (!) real value is '' RedirectPolicy = None # (!) real value is '' RedirectPolicyAttribute = None # (!) real value is '' ResourceTypeAttribute = None # (!) real value is '' SameOriginRedirectPolicy = None # (!) real value is '' ServerHeader = None # (!) real value is '' SetCookieHeader = None # (!) real value is '' SourceIsFromCacheAttribute = None # (!) real value is '' SpdyAllowedAttribute = None # (!) real value is '' SpdyWasUsedAttribute = None # (!) real value is '' SynchronousRequestAttribute = None # (!) real value is '' User = None # (!) real value is '' UserAgentHeader = None # (!) real value is '' UserMax = None # (!) real value is '' UserVerifiedRedirectPolicy = None # (!) real value is '' __hash__ = None

[ "siddharthnatamai@gmail.com" ]

siddharthnatamai@gmail.com

e619cceed7ad73fb07942df520efdbcc1f04a953

163bbb4e0920dedd5941e3edfb2d8706ba75627d

/Code/CodeRecords/2570/60618/303481.py

0337b9b984df63071c855f8763aef609192d23b7

[]

no_license

AdamZhouSE/pythonHomework

a25c120b03a158d60aaa9fdc5fb203b1bb377a19

ffc5606817a666aa6241cfab27364326f5c066ff

refs/heads/master

2022-11-24T08:05:22.122011

2020-07-28T16:21:24

259,576,640

2

1

null

UTF-8

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false

531

py

from bisect import bisect_left n=int(input()) arr=[[0]*2]*n for i in range(0,n): arr[i]=[int(k) for k in input().split(",")] # sort increasing in first dimension and decreasing on second arr.sort(key=lambda x: (x[0], -x[1])) def lis(nums): dp = [] for i in range(len(nums)): idx = bisect_left(dp, nums[i]) if idx == len(dp): dp.append(nums[i]) else: dp[idx] = nums[i] return len(dp) # extract the second dimension and run the LIS return lis([i[1] for i in arr])

[ "1069583789@qq.com" ]

1069583789@qq.com

0a7b49b4e997fd25af6ea472f4e98a232abd3f33

597c3a6200867b45b45b7f33ee020bfa91aede5d

/Week-1024/879.py

02d46ee3996da11cbfb581d23007f55e65f568e6

[]

no_license

Bieneath/LeetCode_training

997251387f9faf7c1301cbc9900d3fbfcc7a7a37

822747436c3499c802b90fab2577577309e2f5b7

refs/heads/master

2023-05-09T21:30:36.409743

2021-06-15T15:22:34

377,205,044

0

null

UTF-8

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920

py

# 二维DP算法 https://leetcode.com/problems/profitable-schemes/discuss/154617/C%2B%2BJavaPython-DP # 这题基本思路不难，类似搭桥问题，计划方案“2人3收益”相当于桥梁，dp[i+3][j+2]的方案数能继承自dp[i][j]通过此方案。但是这题细节方面比较难想。比如这里为什么要反向遍历？原因是当前dp[i][j]需要由dp[i-?][j-?]计算获得，同时这里有个时序性，新的方案要在之前方案实施结果之上计算得出。 class Solution: def profitableSchemes(self, n: int, target: int, group: List[int], profit: List[int]) -> int: dp = [[0] * (n + 1) for _ in range(target + 1)] dp[0][0] = 1 for g, p in zip(group, profit): for i in range(target, -1, -1): for j in range(n - g, -1, -1): dp[min(target, i + p)][j + g] += dp[i][j] return sum(dp[target]) % (10**9 + 7)

[ "wulijieru@gmail.com" ]

wulijieru@gmail.com

7908104ec0c51de2f7300174a01e4037848a0656

9430ebd88984bf5b5fdbca90988d03e45c5fb78f

/apps/app/admin.py

e4aa5b8eeb8b88ef17387bb43f237d144b59330b

[]

no_license

osw4l/liveset-api

6beb05e7f1ce52fe5ef1e6dc0615f6a0a9312e83

a72f0b86f1f452b577c10f195ecb6d28c2ee5c07

refs/heads/master

2022-12-11T20:48:54.295538

2019-09-16T14:01:00

207,845,311

1

0

null

2022-07-15T20:31:03

2019-09-11T15:26:20

Python

UTF-8

Python

false

485

py

from django.contrib import admin from . import models # Register your models here. admin.site.site_header = 'LiveSet Admin' admin.site.site_title = 'LiveSet Admin' admin.site.index_title = 'LiveSet Admin' COMMON_LIST_DISPLAY = ['id', 'name', 'order', 'file', 'active'] @admin.register(models.Song) class SongAdmin(admin.ModelAdmin): list_display = COMMON_LIST_DISPLAY @admin.register(models.Video) class VideoAdmin(admin.ModelAdmin): list_display = COMMON_LIST_DISPLAY

[ "ioswxd@gmail.com" ]

ioswxd@gmail.com

d04c6ba42829c8b9e5a5013b0e250ab5033003eb

e32bb97b6b18dfd48760ed28553a564055878d48

/source_py3/python_toolbox/nifty_collections/frozen_counter.py

fd7ef390df0b1a0045e8ed9d52e4159678f1f422

[ "MIT" ]

permissive

rfdiazpr/python_toolbox

26cb37dd42342c478931699b00d9061aedcd924a

430dd842ed48bccdb3a3166e91f76bd2aae75a88

refs/heads/master

2020-12-31T04:15:53.977935

2014-04-30T23:54:58

null

0

null

UTF-8

Python

false

7,032

py

# Copyright 2009-2014 Ram Rachum., # This program is distributed under the MIT license. import operator import heapq import itertools import collections from .frozen_dict import FrozenDict try: # Load C helper function if available from _collections import _count_elements except ImportError: def _count_elements(mapping, iterable): '''Tally elements from the iterable.''' mapping_get = mapping.get for element in iterable: mapping[element] = mapping_get(element, 0) + 1 class FrozenCounter(FrozenDict): ''' An immutable counter. A counter that can't be changed. The advantage of this over `collections.Counter` is mainly that it's hashable, and thus can be used as a key in dicts and sets. In other words, `FrozenCounter` is to `Counter` what `frozenset` is to `set`. ''' def __init__(self, iterable=None, **kwargs): super().__init__() if iterable is not None: if isinstance(iterable, collections.Mapping): self._dict.update(iterable) else: _count_elements(self._dict, iterable) if kwargs: self._dict.update(kwargs) for key, value in self.items(): if value == 0: del self._dict[key] __getitem__ = lambda self, key: self._dict.get(key, 0) def most_common(self, n=None): ''' List the `n` most common elements and their counts, sorted. Results are sorted from the most common to the least. If `n is None`, then list all element counts. >>> FrozenCounter('abcdeabcdabcaba').most_common(3) [('a', 5), ('b', 4), ('c', 3)] ''' # Emulate Bag.sortedByCount from Smalltalk if n is None: return sorted(self.items(), key=operator.itemgetter(1), reverse=True) return heapq.nlargest(n, self.items(), key=operator.itemgetter(1)) def elements(self): ''' Iterate over elements repeating each as many times as its count. >>> c = FrozenCounter('ABCABC') >>> sorted(c.elements()) ['A', 'A', 'B', 'B', 'C', 'C'] # Knuth's example for prime factors of 1836: 2**2 * 3**3 * 17**1 >>> prime_factors = FrozenCounter({2: 2, 3: 3, 17: 1}) >>> product = 1 >>> for factor in prime_factors.elements(): # loop over factors ... product *= factor # and multiply them >>> product 1836 Note, if an element's count has been set to zero or is a negative number, `.elements()` will ignore it. ''' # Emulate Bag.do from Smalltalk and Multiset.begin from C++. return itertools.chain.from_iterable( itertools.starmap(itertools.repeat, self.items()) ) @classmethod def fromkeys(cls, iterable, v=None): # There is no equivalent method for counters because setting v=1 # means that no element can have a count greater than one. raise NotImplementedError( 'FrozenCounter.fromkeys() is undefined. Use ' 'FrozenCounter(iterable) instead.' ) def __repr__(self): if not self: return '%s()' % self.__class__.__name__ try: items = ', '.join(map('%r: %r'.__mod__, self.most_common())) return '%s({%s})' % (self.__class__.__name__, items) except TypeError: # handle case where values are not orderable return '{0}({1!r})'.format(self.__class__.__name__, dict(self)) __pos__ = lambda self: self __neg__ = lambda self: type(self)({key: -value for key, value in self.items()}) # Multiset-style mathematical operations discussed in: # Knuth TAOCP Volume II section 4.6.3 exercise 19 # and at http://en.wikipedia.org/wiki/Multiset # # Outputs guaranteed to only include positive counts. # # To strip negative and zero counts, add-in an empty counter: # c += FrozenCounter() def __add__(self, other): ''' Add counts from two counters. >>> FrozenCounter('abbb') + FrozenCounter('bcc') FrozenCounter({'b': 4, 'c': 2, 'a': 1}) ''' if not isinstance(other, FrozenCounter): return NotImplemented result = collections.Counter() for element, count in self.items(): new_count = count + other[element] if new_count > 0: result[element] = new_count for element, count in other.items(): if element not in self and count > 0: result[element] = count return FrozenCounter(result) def __sub__(self, other): ''' Subtract count, but keep only results with positive counts. >>> FrozenCounter('abbbc') - FrozenCounter('bccd') FrozenCounter({'b': 2, 'a': 1}) ''' if not isinstance(other, FrozenCounter): return NotImplemented result = collections.Counter() for element, count in self.items(): new_count = count - other[element] if new_count > 0: result[element] = new_count for element, count in other.items(): if element not in self and count < 0: result[element] = 0 - count return FrozenCounter(result) def __or__(self, other): ''' Get the maximum of value in either of the input counters. >>> FrozenCounter('abbb') | FrozenCounter('bcc') FrozenCounter({'b': 3, 'c': 2, 'a': 1}) ''' if not isinstance(other, FrozenCounter): return NotImplemented result = collections.Counter() for element, count in self.items(): other_count = other[element] new_count = other_count if count < other_count else count if new_count > 0: result[element] = new_count for element, count in other.items(): if element not in self and count > 0: result[element] = count return FrozenCounter(result) def __and__(self, other): ''' Get the minimum of corresponding counts. >>> FrozenCounter('abbb') & FrozenCounter('bcc') FrozenCounter({'b': 1}) ''' if not isinstance(other, FrozenCounter): return NotImplemented result = collections.Counter() for element, count in self.items(): other_count = other[element] new_count = count if count < other_count else other_count if new_count > 0: result[element] = new_count return FrozenCounter(result)

[ "ram@rachum.com" ]

ram@rachum.com

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""" Pharos.Model.laser._skeleton.py ================================== .. note:: **IMPORTANT** Whatever new function is implemented in a specific model, it should be first declared in the laserBase class. In this way the other models will have access to the method and the program will keep running (perhaps with non intended behavior though). .. sectionauthor:: Aquiles Carattino <aquiles@uetke.com> """ class LaserBase(): # Trigger modes TRIG_NO = 0 TRIG_EXTERNAL = 1 TRIG_SOFTWARE = 2 TRIG_OUTPUT = 3 # Scan modes MODE_SINGLE = 1 MODE_TWO_WAY = 2 MODE_STEP_SINGLE = 3 MODE_STEP_TWO_WAY = 4 # Parameters (wavelength or frequency) PARAM_WAVELENGTH = 1 PARAM_FREQUENCY = 2 def __init__(self): self.trig_mode = self.TRIG_NO # Means the trigger was not set. def wavelength_scan_setup(self, start, end, steps, time, trigger, mode): pass def frequency_scan_setup(self, start, end, steps, time, trigger, mode): pass def trigger_scan(self): pass def is_running(self): pass def stop_scan(self): pass

[ "aquiles@aquicarattino.com" ]

aquiles@aquicarattino.com

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/ros_catkin_ws/build_isolated/catkin/catkin_generated/generate_cached_setup.py

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# -*- coding: utf-8 -*- from __future__ import print_function import argparse import os import stat import sys # find the import for catkin's python package - either from source space or from an installed underlay if os.path.exists(os.path.join('/root/ros_catkin_ws/src/catkin/cmake', 'catkinConfig.cmake.in')): sys.path.insert(0, os.path.join('/root/ros_catkin_ws/src/catkin/cmake', '..', 'python')) try: from catkin.environment_cache import generate_environment_script except ImportError: # search for catkin package in all workspaces and prepend to path for workspace in "".split(';'): python_path = os.path.join(workspace, 'lib/python2.7/dist-packages') if os.path.isdir(os.path.join(python_path, 'catkin')): sys.path.insert(0, python_path) break from catkin.environment_cache import generate_environment_script code = generate_environment_script('/root/ros_catkin_ws/devel_isolated/catkin/env.sh') output_filename = '/root/ros_catkin_ws/build_isolated/catkin/catkin_generated/setup_cached.sh' with open(output_filename, 'w') as f: #print('Generate script for cached setup "%s"' % output_filename) f.write('\n'.join(code)) mode = os.stat(output_filename).st_mode os.chmod(output_filename, mode | stat.S_IXUSR)

[ "simon.trendel@tum.de" ]

simon.trendel@tum.de

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/day18/threadingDemo.py

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[]

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# _*_ coding : UTF-8 _*_ # 开发人员 : ChangYw # 开发时间 : 2019/8/7 14:17 # 文件名称 : threadingDemo.PY # 开发工具 : PyCharm #创建线程 import threading import time import random # def foo(info): # # 每个线程都会有个ID # print("线程ID:",threading.get_ident()) # # 当前线程名字 # print(threading.current_thread()) # # 当前线程所在进程下，活的线程数目 # print(threading.active_count()) # print("%s : abcdef"%info) # # t = threading.Thread(target=foo,name="FirstThread",args=("first thread demo",)) # # t.start() # # def addnum(): # m = 0 # for i in range(1,101): # m += i # print("m: ",m) # # 每个线程都会有个ID # print("线程ID:", threading.get_ident()) # # 当前线程名字 # print(threading.current_thread()) # # 当前线程所在进程下，活的线程数目 # print(threading.active_count()) # # t1 = threading.Thread(target=addnum,name="addNumThread" ) # t1.start() # # s_name = "常译文" # # def show(tname) : # print(tname,end=" : ") # while True: # for c in s_name: # print(c,end="") # print() # # # #show("demo") # threading.Thread(target=show,name = "C1",args=("thread-1",)).start() # threading.Thread(target=show,name = "C2",args=("thread-2",)).start() class MyThread(threading.Thread): def __init__(self,info): super().__init__() self.info = info def run(self): print(self.info) time.sleep(2) print("当前存活的线程数目：%d"%threading.active_count()) print(threading.current_thread()," ending...") if __name__ == '__main__': start_time = time.time() t1 = MyThread("Hello World!") t2 = MyThread("Heelo Python!") t1.start() t2.start() t1.join() t2.join() print("main : 当前存活的线程数目：%d !" % threading.active_count()) print("main threading ...........") end_time = time.time() print("运行时间：",start_time-end_time)

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# Copyright 2015 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. from core import perf_benchmark from measurements import startup import page_sets from telemetry import benchmark class _StartupWarm(perf_benchmark.PerfBenchmark): """Measures warm startup time with a clean profile.""" options = {'pageset_repeat': 5} @classmethod def Name(cls): return 'chrome_signin_starup' def CreatePageTest(self, options): return startup.Startup(cold=False) @benchmark.Disabled('all') # crbug.com/551938 # On android logging in is done through system accounts workflow. @benchmark.Disabled('android') class SigninStartup(_StartupWarm): """Measures warm startup time of signing a profile into Chrome.""" page_set = page_sets.ChromeSigninPageSet @classmethod def Name(cls): return 'startup.warm.chrome_signin'

[ "enrico.weigelt@gr13.net" ]

enrico.weigelt@gr13.net

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import tensorflow as tf from tensorflow.keras import Model from openrec.tf2.modules import LatentFactor, PairwiseLogLoss class BPR(Model): def __init__(self, dim_user_embed, dim_item_embed, total_users, total_items): super(BPR, self).__init__() self.user_latent_factor = LatentFactor(num_instances=total_users, dim=dim_user_embed, name='user_latent_factor') self.item_latent_factor = LatentFactor(num_instances=total_items, dim=dim_item_embed, name='item_latent_factor') self.item_bias = LatentFactor(num_instances=total_items, dim=1, name='item_bias') self.pairwise_log_loss = PairwiseLogLoss() def call(self, user_id, p_item_id, n_item_id): user_vec = self.user_latent_factor(user_id) p_item_vec = self.item_latent_factor(p_item_id) p_item_bias = self.item_bias(p_item_id) n_item_vec = self.item_latent_factor(n_item_id) n_item_bias = self.item_bias(n_item_id) loss = self.pairwise_log_loss(user_vec=user_vec, p_item_vec=p_item_vec, p_item_bias=p_item_bias, n_item_vec=n_item_vec, n_item_bias=n_item_bias) l2_loss = tf.nn.l2_loss(user_vec) + tf.nn.l2_loss(p_item_vec) + tf.nn.l2_loss(n_item_vec) return loss, l2_loss def inference(self, user_id): user_vec = self.user_latent_factor(user_id) return tf.linalg.matmul(user_vec, self.item_latent_factor.variables[0], transpose_b=True) + \ tf.reshape(self.item_bias.variables[0], [-1])

[ "ylongqi@gmail.com" ]

ylongqi@gmail.com

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/scripts/stringio-example-1.py

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mtslong/demo

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import StringIO MESSAGE = "That man is depriving a village somewhere of a computer scientist." file = StringIO.StringIO(MESSAGE) print file.read() ## That man is depriving a village somewhere of a computer scientist.

[ "mofeng@netease.com" ]

mofeng@netease.com

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/Projects/Object-Oriented Python/s4v3/yatzy/dice.py

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import random class Die: def __init__(self, sides=2, value=0): if not sides >= 2: raise ValueError("Must have at least 2 sides") if not isinstance(sides, int): raise ValueError("Sides must be a whole number") self.value = value or random.randint(1, sides) def __int__(self): return self.value def __eq__(self, other): return int(self) == other def __ne__(self, other): return int(self) != other def __gt__(self, other): return int(self) > other def __lt__(self, other): return int(self) < other def __ge__(self, other): return int(self) > other or int(self) == other def __le__(self, other): return int(self) < other or int(self) == other def __add__(self, other): return int(self) + other def __radd__(self, other): return int(self) + other class D6(Die): def __init__(self, value=0): super().__init__(sides=6, value=value)

[ "isamu3636136@gmail.com" ]

isamu3636136@gmail.com

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"""Copyright (c) 2015 Russell HarkansonSee the file LICENSE.txt for copying permission.""" import sys if sys.version < '3': print("Error: Python 3+ required to run Pyriscope.") sys.exit(1) from pyriscope import processor def main(args=None): if args is None: args = sys.argv[1:] if len(args) == 1 and args[0] == "__magic__": args = input("Enter args now: ").strip(' ').split(' ') processor.process(args) if __name__ == "__main__": main()

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thaisnviana@gmail.com

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# Copyright (c) 2017-present, Facebook, Inc. # All rights reserved. # # This source code is licensed under the license found in the LICENSE file in # the root directory of this source tree. An additional grant of patent rights # can be found in the PATENTS file in the same directory. import torch import torch.nn.functional as F from fairseq import utils from .conv_tbc import ConvTBC class LinearizedConvolution(ConvTBC): """An optimized version of nn.Conv1d. At training time, this module uses ConvTBC, which is an optimized version of Conv1d. At inference time, it optimizes incremental generation (i.e., one time step at a time) by replacing the convolutions with linear layers. Note that the input order changes from training to inference. """ def __init__(self, in_channels, out_channels, kernel_size, **kwargs): super().__init__(in_channels, out_channels, kernel_size, **kwargs) self._linearized_weight = None self.register_backward_hook(self._clear_linearized_weight) def forward(self, input, incremental_state=None): """ Input: Time x Batch x Channel during training Batch x Time x Channel during inference Args: incremental_state: Used to buffer signal; if not None, then input is expected to contain a single frame. If the input order changes between time steps, call reorder_incremental_state. """ if incremental_state is None: output = super().forward(input) if self.kernel_size[0] > 1 and self.padding[0] > 0: # remove future timesteps added by padding output = output[:-self.padding[0], :, :] return output # reshape weight weight = self._get_linearized_weight() kw = self.kernel_size[0] bsz = input.size(0) # input: bsz x len x dim if kw > 1: input = input.data input_buffer = self._get_input_buffer(incremental_state) if input_buffer is None: input_buffer = input.new(bsz, kw, input.size(2)).zero_() self._set_input_buffer(incremental_state, input_buffer) else: # shift buffer input_buffer[:, :-1, :] = input_buffer[:, 1:, :].clone() # append next input input_buffer[:, -1, :] = input[:, -1, :] input = input_buffer with torch.no_grad(): output = F.linear(input.view(bsz, -1), weight, self.bias) return output.view(bsz, 1, -1) def reorder_incremental_state(self, incremental_state, new_order): input_buffer = self._get_input_buffer(incremental_state) if input_buffer is not None: input_buffer = input_buffer.index_select(0, new_order) self._set_input_buffer(incremental_state, input_buffer) def _get_input_buffer(self, incremental_state): return utils.get_incremental_state(self, incremental_state, 'input_buffer') def _set_input_buffer(self, incremental_state, new_buffer): return utils.set_incremental_state(self, incremental_state, 'input_buffer', new_buffer) def _get_linearized_weight(self): if self._linearized_weight is None: kw = self.kernel_size[0] weight = self.weight.transpose(2, 1).transpose(1, 0).contiguous() assert weight.size() == (self.out_channels, kw, self.in_channels) self._linearized_weight = weight.view(self.out_channels, -1) return self._linearized_weight def _clear_linearized_weight(self, *args): self._linearized_weight = None

[ "vbittorf@google.com" ]

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/WebMirror/management/rss_parser_funcs/feed_parse_extractLogatseTranslations.py

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def extractLogatseTranslations(item): """ 'Logatse Translations' """ vol, chp, frag, postfix = extractVolChapterFragmentPostfix(item['title']) if not (chp or vol or frag) or 'preview' in item['title'].lower(): return None return False

[ "something@fake-url.com" ]

something@fake-url.com

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from xai.brain.wordbase.nouns._arboretum import _ARBORETUM #calss header class _ARBORETA(_ARBORETUM, ): def __init__(self,): _ARBORETUM.__init__(self) self.name = "ARBORETA" self.specie = 'nouns' self.basic = "arboretum" self.jsondata = {}

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

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# -*- coding: utf-8 -*- # # Copyright (C) 2009-2018 the sqlparse authors and contributors # <see AUTHORS file> # # This module is part of python-sqlparse and is released under # the BSD License: https://opensource.org/licenses/BSD-3-Clause from sqlparse import sql, tokens as T from sqlparse.compat import text_type from sqlparse.utils import offset, indent class AlignedIndentFilter(object): join_words = (r'((LEFT\s+|RIGHT\s+|FULL\s+)?' r'(INNER\s+|OUTER\s+|STRAIGHT\s+)?|' r'(CROSS\s+|NATURAL\s+)?)?JOIN\b') by_words = r'(GROUP|ORDER)\s+BY\b' split_words = ('FROM', join_words, 'ON', by_words, 'WHERE', 'AND', 'OR', 'HAVING', 'LIMIT', 'UNION', 'VALUES', 'SET', 'BETWEEN', 'EXCEPT') def __init__(self, char=' ', n='\n'): self.n = n self.offset = 0 self.indent = 0 self.char = char self._max_kwd_len = len('select') def nl(self, offset=1): # offset = 1 represent a single space after SELECT offset = -len(offset) if not isinstance(offset, int) else offset # add two for the space and parenthesis indent = self.indent * (2 + self._max_kwd_len) return sql.Token(T.Whitespace, self.n + self.char * ( self._max_kwd_len + offset + indent + self.offset)) def _process_statement(self, tlist): if len(tlist.tokens) > 0 and tlist.tokens[0].is_whitespace \ and self.indent == 0: tlist.tokens.pop(0) # process the main query body self._process(sql.TokenList(tlist.tokens)) def _process_parenthesis(self, tlist): # if this isn't a subquery, don't re-indent _, token = tlist.token_next_by(m=(T.DML, 'SELECT')) if token is not None: with indent(self): tlist.insert_after(tlist[0], self.nl('SELECT')) # process the inside of the parenthesis self._process_default(tlist) # de-indent last parenthesis tlist.insert_before(tlist[-1], self.nl()) def _process_identifierlist(self, tlist): # columns being selected identifiers = list(tlist.get_identifiers()) identifiers.pop(0) [tlist.insert_before(token, self.nl()) for token in identifiers] self._process_default(tlist) def _process_case(self, tlist): offset_ = len('case ') + len('when ') cases = tlist.get_cases(skip_ws=True) # align the end as well end_token = tlist.token_next_by(m=(T.Keyword, 'END'))[1] cases.append((None, [end_token])) condition_width = [len(' '.join(map(text_type, cond))) if cond else 0 for cond, _ in cases] max_cond_width = max(condition_width) for i, (cond, value) in enumerate(cases): # cond is None when 'else or end' stmt = cond[0] if cond else value[0] if i > 0: tlist.insert_before(stmt, self.nl( offset_ - len(text_type(stmt)))) if cond: ws = sql.Token(T.Whitespace, self.char * ( max_cond_width - condition_width[i])) tlist.insert_after(cond[-1], ws) def _next_token(self, tlist, idx=-1): split_words = T.Keyword, self.split_words, True tidx, token = tlist.token_next_by(m=split_words, idx=idx) # treat "BETWEEN x and y" as a single statement if token and token.normalized == 'BETWEEN': tidx, token = self._next_token(tlist, tidx) if token and token.normalized == 'AND': tidx, token = self._next_token(tlist, tidx) return tidx, token def _split_kwds(self, tlist): tidx, token = self._next_token(tlist) while token: # joins, group/order by are special case. only consider the first # word as aligner if ( token.match(T.Keyword, self.join_words, regex=True) or token.match(T.Keyword, self.by_words, regex=True) ): token_indent = token.value.split()[0] else: token_indent = text_type(token) tlist.insert_before(token, self.nl(token_indent)) tidx += 1 tidx, token = self._next_token(tlist, tidx) def _process_default(self, tlist): self._split_kwds(tlist) # process any sub-sub statements for sgroup in tlist.get_sublists(): idx = tlist.token_index(sgroup) pidx, prev_ = tlist.token_prev(idx) # HACK: make "group/order by" work. Longer than max_len. offset_ = 3 if ( prev_ and prev_.match(T.Keyword, self.by_words, regex=True) ) else 0 with offset(self, offset_): self._process(sgroup) def _process(self, tlist): func_name = '_process_{cls}'.format(cls=type(tlist).__name__) func = getattr(self, func_name.lower(), self._process_default) func(tlist) def process(self, stmt): self._process(stmt) return stmt

[ "rizwansoaib@gmail.com" ]

rizwansoaib@gmail.com

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DiptoChakrabarty/Python

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2020-04-21T18:05:49.000026

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import subprocess as sp import pyttsx3 as py print("\t\t\t Gods Menu ") speaker=py.init() while True: print("Enter Choice") print(""" 1) Date 2)Calendar 3)Yell """) speaker.say("Enter Your Choice") speaker.runAndWait() ch=int(input()) if(ch==1): speaker.say("The Date is") speaker.runAndWait() x= sp.getoutput("date") print(x) elif(ch==2): speaker.say("The Calendar is") speaker.runAndWait() x=sp.getoutput("cal") print(x) elif(ch==3): print("Yipeeee") speaker.say("yipeeeeeeeeeeeeeeee") speaker.runAndWait() else: break

[ "diptochuck123@gmail.com" ]

diptochuck123@gmail.com

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/web/dispatch/object/release.py

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"""Release information about Object Dispatch.""" from collections import namedtuple version_info = namedtuple('version_info', ('major', 'minor', 'micro', 'releaselevel', 'serial'))(3, 0, 0, 'final', 0) version = ".".join([str(i) for i in version_info[:3]]) + ((version_info.releaselevel[0] + str(version_info.serial)) if version_info.releaselevel != 'final' else '') author = namedtuple('Author', ['name', 'email'])("Alice Bevan-McGregor", 'alice@gothcandy.com') description = "Object dispatch; a method to resolve path components to Python objects using directed attribute access." copyright = "2009-2019, Alice Bevan-McGregor and contributors" url = 'https://github.com/marrow/web.dispatch.object'

[ "alice@gothcandy.com" ]

alice@gothcandy.com

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/.history/mergeSort_20200731130122.py

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[]

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MaryanneNjeri/pythonModules

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# MERGE SORT # --> Recursive # ---> divide and conquer # ---> If the problem is too big , break it down # --> if its a single def merge(arr):

[ "mary.jereh@gmail.com" ]

mary.jereh@gmail.com

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/df_cart/migrations/0001_initial.py

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[]

no_license

2339379789/zhang_ttshop

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# -*- coding: utf-8 -*- # Generated by Django 1.10.6 on 2018-03-21 12:48 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ('df_goods', '0002_auto_20180321_1141'), ('df_user', '0001_initial'), ] operations = [ migrations.CreateModel( name='CartInfo', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('count', models.IntegerField(default=0)), ('goods', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='df_goods.GoodsInfo')), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='df_user.UserInfo')), ], ), ]

[ "2339379789@qq.com.com" ]

2339379789@qq.com.com

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rmanzoni/HTT

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refs/heads/master

2016-09-06T05:55:52.602604

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import FWCore.ParameterSet.Config as cms import os,sys sys.path.append('/afs/cern.ch/user/m/manzoni/summer13/CMGTools/CMSSW_5_3_9/src/CMGTools/H2TauTau/prod/25aug_corrMC/up/mc/DYJetsToLL_M-50_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM/V5_B/PAT_CMG_V5_16_0_1377544840/HTT_24Jul_newTES_manzoni_Up_Jobs') from base_cfg import * process.source = cms.Source("PoolSource", noEventSort = cms.untracked.bool(True), inputCommands = cms.untracked.vstring('keep *', 'drop cmgStructuredPFJets_cmgStructuredPFJetSel__PAT'), duplicateCheckMode = cms.untracked.string('noDuplicateCheck'), fileNames = cms.untracked.vstring('/store/cmst3/user/cmgtools/CMG/DYJetsToLL_M-50_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM/V5_B/PAT_CMG_V5_16_0/cmgTuple_1404.root', '/store/cmst3/user/cmgtools/CMG/DYJetsToLL_M-50_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM/V5_B/PAT_CMG_V5_16_0/cmgTuple_1405.root', '/store/cmst3/user/cmgtools/CMG/DYJetsToLL_M-50_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM/V5_B/PAT_CMG_V5_16_0/cmgTuple_1406.root', '/store/cmst3/user/cmgtools/CMG/DYJetsToLL_M-50_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM/V5_B/PAT_CMG_V5_16_0/cmgTuple_1407.root', '/store/cmst3/user/cmgtools/CMG/DYJetsToLL_M-50_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM/V5_B/PAT_CMG_V5_16_0/cmgTuple_1408.root') )

[ "riccardo.manzoni@cern.ch" ]

riccardo.manzoni@cern.ch

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/project_scrapy/spiders/sony.py

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[]

no_license

sushma535/WebSites

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import scrapy from scrapy.crawler import CrawlerProcess import os import csv from csv import reader import re total_data = {} class SimilarWeb(scrapy.Spider): name = 'SW' user_agent = 'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/44.0.2403.157 Safari/537.36' start_urls = ['https://www.sony.com/en/', 'https://www.similarsites.com/site/sony.com/'] csv_columns = ['Category', 'Description', 'Name', 'Url'] csv_file = 'websites1_data.csv' count = 0 def parse(self, response): data, desc, cat = '', '', '' print('response url:', response.url) if response.url == self.start_urls[0]: data = response.css('title::text').get() if data: data = re.sub("\n\t\t", '', data) total_data['Name'] = data self.count += 1 elif response.url == self.start_urls[1]: cat = response.css( 'div[class="StatisticsCategoriesDistribution__CategoryTitle-fnuckk-6 jsMDeK"]::text').getall() desc = response.css('div[class="SiteHeader__Description-sc-1ybnx66-8 hhZNQm"]::text').get() if cat: cat = ": ".join(cat[:]) total_data['Category'] = cat total_data['Description'] = desc total_data['Url'] = self.start_urls[0] self.count += 1 if self.count == 2: print("total data", total_data) new_data = [total_data['Category'], total_data['Description'], total_data['Name'], total_data['Url']] print("new data", new_data) self.row_appending_to_csv_file(new_data) def row_appending_to_csv_file(self, data): if os.path.exists(self.csv_file): need_to_add_headers = False with open(self.csv_file, 'a+', newline='') as file: file.seek(0) csv_reader = reader(file) if len(list(csv_reader)) == 0: need_to_add_headers = True csv_writer = csv.writer(file) if need_to_add_headers: csv_writer.writerow(self.csv_columns) csv_writer.writerow(data) else: with open(self.csv_file, 'w', newline='') as file: csv_writer = csv.writer(file) csv_writer.writerow(self.csv_columns) # header csv_writer.writerow(data) process = CrawlerProcess() process.crawl(SimilarWeb) process.start()

[ "sushmakusumareddy@gmail.com" ]

sushmakusumareddy@gmail.com

ccfde10e9450e03a564e8089cb6cd056121cdde5

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/wincewebkit/WebKitTools/Scripts/webkitpy/common/system/user.py

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[]

no_license

datadiode/WinCEWebKit

3586fac69ba7ce9efbde42250266ddbc5c920c5e

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refs/heads/master

2023-03-15T23:47:30.374484

2014-08-14T14:41:13

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# Copyright (c) 2009, Google Inc. All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are # met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above # copyright notice, this list of conditions and the following disclaimer # in the documentation and/or other materials provided with the # distribution. # * Neither the name of Google Inc. nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR # A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT # OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, # SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT # LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, # DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY # THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import logging import os import re import shlex import subprocess import sys import webbrowser _log = logging.getLogger("webkitpy.common.system.user") try: import readline except ImportError: if sys.platform != "win32": # There is no readline module for win32, not much to do except cry. _log.warn("Unable to import readline.") # FIXME: We could give instructions for non-mac platforms. # Lack of readline results in a very bad user experiance. if sys.platform == "mac": _log.warn("If you're using MacPorts, try running:") _log.warn(" sudo port install py25-readline") class User(object): DEFAULT_NO = 'n' DEFAULT_YES = 'y' # FIXME: These are @classmethods because bugzilla.py doesn't have a Tool object (thus no User instance). @classmethod def prompt(cls, message, repeat=1, raw_input=raw_input): response = None while (repeat and not response): repeat -= 1 response = raw_input(message) return response @classmethod def prompt_with_list(cls, list_title, list_items, can_choose_multiple=False, raw_input=raw_input): print list_title i = 0 for item in list_items: i += 1 print "%2d. %s" % (i, item) # Loop until we get valid input while True: if can_choose_multiple: response = cls.prompt("Enter one or more numbers (comma-separated), or \"all\": ", raw_input=raw_input) if not response.strip() or response == "all": return list_items try: indices = [int(r) - 1 for r in re.split("\s*,\s*", response)] except ValueError, err: continue return [list_items[i] for i in indices] else: try: result = int(cls.prompt("Enter a number: ", raw_input=raw_input)) - 1 except ValueError, err: continue return list_items[result] def edit(self, files): editor = os.environ.get("EDITOR") or "vi" args = shlex.split(editor) # Note: Not thread safe: http://bugs.python.org/issue2320 subprocess.call(args + files) def _warn_if_application_is_xcode(self, edit_application): if "Xcode" in edit_application: print "Instead of using Xcode.app, consider using EDITOR=\"xed --wait\"." def edit_changelog(self, files): edit_application = os.environ.get("CHANGE_LOG_EDIT_APPLICATION") if edit_application and sys.platform == "darwin": # On Mac we support editing ChangeLogs using an application. args = shlex.split(edit_application) print "Using editor in the CHANGE_LOG_EDIT_APPLICATION environment variable." print "Please quit the editor application when done editing." self._warn_if_application_is_xcode(edit_application) subprocess.call(["open", "-W", "-n", "-a"] + args + files) return self.edit(files) def page(self, message): pager = os.environ.get("PAGER") or "less" try: # Note: Not thread safe: http://bugs.python.org/issue2320 child_process = subprocess.Popen([pager], stdin=subprocess.PIPE) child_process.communicate(input=message) except IOError, e: pass def confirm(self, message=None, default=DEFAULT_YES, raw_input=raw_input): if not message: message = "Continue?" choice = {'y': 'Y/n', 'n': 'y/N'}[default] response = raw_input("%s [%s]: " % (message, choice)) if not response: response = default return response.lower() == 'y' def can_open_url(self): try: webbrowser.get() return True except webbrowser.Error, e: return False def open_url(self, url): if not self.can_open_url(): _log.warn("Failed to open %s" % url) webbrowser.open(url)

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achellies@163.com

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/tests/test_tapioca_jarbas.py

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giovanisleite/tapioca-jarbas

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refs/heads/master

2021-05-07T19:11:55.541940

2017-02-18T21:29:48

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import pytest from tapioca_jarbas import Jarbas @pytest.fixture def wrapper(): return Jarbas() def test_resource_access(wrapper): resource = wrapper.reimbursement_list() assert resource.data == 'http://jarbas.datasciencebr.com/api/reimbursement/'

[ "daniloshiga@gmail.com" ]

daniloshiga@gmail.com

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daekeun-ml/smdalle

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refs/heads/master

2023-05-03T05:57:56.346613

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import io import sys import os, sys import requests import PIL import warnings import os import hashlib import urllib import yaml from pathlib import Path from tqdm import tqdm from math import sqrt from omegaconf import OmegaConf from taming.models.vqgan import VQModel import torch from torch import nn import torch.nn.functional as F from einops import rearrange from dalle_pytorch import distributed_utils # constants CACHE_PATH = os.path.expanduser("~/.cache/dalle") OPENAI_VAE_ENCODER_PATH = 'https://cdn.openai.com/dall-e/encoder.pkl' OPENAI_VAE_DECODER_PATH = 'https://cdn.openai.com/dall-e/decoder.pkl' VQGAN_VAE_PATH = 'https://heibox.uni-heidelberg.de/f/140747ba53464f49b476/?dl=1' VQGAN_VAE_CONFIG_PATH = 'https://heibox.uni-heidelberg.de/f/6ecf2af6c658432c8298/?dl=1' # helpers methods def exists(val): return val is not None def default(val, d): return val if exists(val) else d def load_model(path): with open(path, 'rb') as f: return torch.load(f, map_location = torch.device('cpu')) def map_pixels(x, eps = 0.1): return (1 - 2 * eps) * x + eps def unmap_pixels(x, eps = 0.1): return torch.clamp((x - eps) / (1 - 2 * eps), 0, 1) def download(args, url, filename = None, root = CACHE_PATH): print(f"args.local_rank : {args.local_rank}") if ( not distributed_utils.is_distributed or args.local_rank == 0 # or distributed_utils.backend.is_local_root_worker() ): os.makedirs(root, exist_ok = True) filename = default(filename, os.path.basename(url)) download_target = os.path.join(root, filename) download_target_tmp = os.path.join(root, f'tmp.{filename}') if os.path.exists(download_target) and not os.path.isfile(download_target): raise RuntimeError(f"{download_target} exists and is not a regular file") if ( distributed_utils.is_distributed and not args.local_rank == 0 # and not distributed_utils.backend.is_local_root_worker() and not os.path.isfile(download_target) ): # If the file doesn't exist yet, wait until it's downloaded by the root worker. distributed_utils.backend.local_barrier() if args.local_rank == 0: if os.path.isfile(download_target): return download_target with urllib.request.urlopen(url) as source, open(download_target_tmp, "wb") as output: with tqdm(total=int(source.info().get("Content-Length")), ncols=80) as loop: while True: buffer = source.read(8192) if not buffer: break output.write(buffer) loop.update(len(buffer)) os.rename(download_target_tmp, download_target) if ( distributed_utils.is_distributed and args.local_rank == 0 # and distributed_utils.backend.is_local_root_worker() ): distributed_utils.backend.local_barrier() return download_target # pretrained Discrete VAE from OpenAI class OpenAIDiscreteVAE(nn.Module): def __init__(self, args): super().__init__() self.enc = load_model(download(args, OPENAI_VAE_ENCODER_PATH)) self.dec = load_model(download(args, OPENAI_VAE_DECODER_PATH)) self.num_layers = 3 self.image_size = 256 self.num_tokens = 8192 @torch.no_grad() def get_codebook_indices(self, img): img = map_pixels(img) z_logits = self.enc.blocks(img) z = torch.argmax(z_logits, dim = 1) return rearrange(z, 'b h w -> b (h w)') def decode(self, img_seq): b, n = img_seq.shape img_seq = rearrange(img_seq, 'b (h w) -> b h w', h = int(sqrt(n))) z = F.one_hot(img_seq, num_classes = self.num_tokens) z = rearrange(z, 'b h w c -> b c h w').float() x_stats = self.dec(z).float() x_rec = unmap_pixels(torch.sigmoid(x_stats[:, :3])) return x_rec def forward(self, img): raise NotImplemented # VQGAN from Taming Transformers paper # https://arxiv.org/abs/2012.09841 class VQGanVAE1024(nn.Module): def __init__(self, args): super().__init__() print(f" ************** VQGanVAE1024 **************** ") model_filename = 'vqgan.1024.model.ckpt' config_filename = 'vqgan.1024.config.yml' download(args, VQGAN_VAE_CONFIG_PATH, config_filename) download(args, VQGAN_VAE_PATH, model_filename) config = OmegaConf.load(str(Path(CACHE_PATH) / config_filename)) model = VQModel(**config.model.params) state = torch.load(str(Path(CACHE_PATH) / model_filename), map_location = 'cpu')['state_dict'] model.load_state_dict(state, strict = False) self.model = model self.num_layers = 4 self.image_size = 256 self.num_tokens = 1024 self._register_external_parameters() def _register_external_parameters(self): """Register external parameters for DeepSpeed partitioning.""" if ( not distributed_utils.is_distributed or not distributed_utils.using_backend( distributed_utils.DeepSpeedBackend) ): return deepspeed = distributed_utils.backend.backend_module deepspeed.zero.register_external_parameter( self, self.model.quantize.embedding.weight) @torch.no_grad() def get_codebook_indices(self, img): b = img.shape[0] img = (2 * img) - 1 _, _, [_, _, indices] = self.model.encode(img) return rearrange(indices, '(b n) () -> b n', b = b) def decode(self, img_seq): b, n = img_seq.shape one_hot_indices = F.one_hot(img_seq, num_classes = self.num_tokens).float() z = (one_hot_indices @ self.model.quantize.embedding.weight) z = rearrange(z, 'b (h w) c -> b c h w', h = int(sqrt(n))) img = self.model.decode(z) img = (img.clamp(-1., 1.) + 1) * 0.5 return img def forward(self, img): raise NotImplemented

[ "dolpal2@gmail.com" ]

dolpal2@gmail.com

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jhabarsingh/LABS

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import io import re import os import sys import string import unicodedata import nltk from nltk.corpus import stopwords import unicodedata from nltk.tokenize import word_tokenize from nltk.stem import PorterStemmer from nltk.stem import WordNetLemmatizer from nltk.tokenize import word_tokenize lemmatizer = WordNetLemmatizer() nltk.download('wordnet') nltk.download('stopwords') DEBUG = False class DataCleaner(): def __init__(self, filename): self.filename = filename self.data = None def getText(self): return self.data def removeSpaces(self, data): return re.sub(' +', ' ', data) def removeNumPun(self, data): data = re.sub(r'\d+', '', data) translator = str.maketrans('', '', string.punctuation) return data.translate(translator) def replaceNewline(self, data): return data.replace('\\n', '\n') def replaceReturnCarrige(self, data): return data.replace('\\r', '') def assignData(self): newData = "" with open(self.filename, "rb") as rfile: newData = rfile.read() self.data = str(newData)[2:-1] self.data = self.removeSpaces(self.data) self.data = self.replaceNewline(self.data) self.data = self.replaceReturnCarrige(self.data) return newData def removeAccent(self): nfkd_form = unicodedata.normalize('NFKD', self.data) return u"".join([c for c in nfkd_form if not unicodedata.combining(c)]) def removestopWord(self): stop_words = set(stopwords.words('english')) words = self.data.split() newData = "" newData = [word for word in words if word not in stopwords.words('english')] return " ".join(newData) def stemming(self): ps = PorterStemmer() words = self.data.split() newData = "" for w in words: newData += ps.stem(w) + " " return newData def lemmatize(self): lm = WordNetLemmatizer() words = self.data.split() newData = "" for w in words: newData += lm.lemmatize(w) + " " return newData def removeSingleLetter(self): data = self.data.split() temp = "" for word in data: if len(word) > 1: temp += word + " " return temp def cleanData(self): self.data = self.removeAccent() self.data = self.removestopWord() self.data = self.removeNumPun(self.data) self.data = self.stemming() self.data = self.lemmatize() self.data = self.removestopWord() self.data = self.removeSingleLetter() return self.data def createFile(self, data): filename =self.filename.split('.')[0] + "_output." + self.filename.split('.')[1] with open(filename, "w+") as wfile: wfile.write(data) os.system(f'mv {filename} outputs') return True def countWords(self, input, output): return len(input.split()) - len(output.split()) if __name__ == "__main__": filename = sys.argv[1] datacleaner = DataCleaner(filename) datacleaner.assignData() input = datacleaner.getText() if DEBUG: print(datacleaner.getText()) changedData = datacleaner.cleanData() datacleaner.createFile(changedData) print(f"File words difference {datacleaner.countWords(input, changedData)}")

[ "jhabarsinghbhati23@gmail.com" ]

jhabarsinghbhati23@gmail.com

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/deepiu/textsum/prepare/default/conf.py

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tangqiqi123/hasky

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IMAGE_FEATURE_LEN = 2048 MAX_EMB_WORDS = 200000 INPUT_TEXT_MAX_WORDS = 30 TEXT_MAX_WORDS = 20 NUM_RESERVED_IDS = 1 ENCODE_UNK = 0

[ "29109317@qq.com" ]

29109317@qq.com

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/app/__init__.py

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permissive

nerevu/hdxscraper-hdro

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# -*- coding: utf-8 -*- """ app ~~~ Provides the flask application """ from __future__ import ( absolute_import, division, print_function, with_statement, unicode_literals) import config from flask import Flask from flask.ext.sqlalchemy import SQLAlchemy __version__ = '0.9.0' __title__ = 'hdxscraper-hdro' __author__ = 'Reuben Cummings' __description__ = ( 'Collector for the UN Human Development Report Office (HDRO) API') __email__ = 'reubano@gmail.com' __license__ = 'MIT' __copyright__ = 'Copyright 2015 Reuben Cummings' db = SQLAlchemy() def create_app(mode=None): app = Flask(__name__) db.init_app(app) if mode: app.config.from_object(getattr(config, mode)) else: app.config.from_envvar('APP_SETTINGS', silent=True) return app

[ "reubano@gmail.com" ]

reubano@gmail.com

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/demo/GazeboMonitor/GazeboMonitor.py

d88abf2b20229ba2f2f6bfe35928c19bdba3c2c1

[]

no_license

dqyi11/SVNBackup

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refs/heads/master

2020-03-26T12:15:01.155873

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''' Created on Apr 22, 2014 @author: walter ''' from MapViewer import * from MapViewForm import * from PyQt4 import QtGui, QtCore import sys if __name__ == '__main__': app = QtGui.QApplication(sys.argv) form = MapViewForm(5) sys.exit(app.exec_())

[ "walter@e224401c-0ce2-47f2-81f6-2da1fe30fd39" ]

walter@e224401c-0ce2-47f2-81f6-2da1fe30fd39

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/examples/introduction.to.programming.with.turtle/windows_only/2-4.triangle2.py

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permissive

royqh1979/PyEasyGraphics

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2021-06-11T10:34:03.001842

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from easygraphics.turtle import * create_world() rt(30); for i in range(3): fd(100) rt(120) lt(30); pause() close_world()

[ "royqh1979@gmail.com" ]

royqh1979@gmail.com

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/puzzle-3/test.py

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mattvenn/oshcamp-treasurehunt

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import unittest import socket import time host = "10.10.0.29" port = 1337 password = 'MK_DCBY07I3YA8]PBVEU' # has good pass embedded bad_pass = 'B3d,P@U^=S<GPc*VNdN\MK_DCBY07I3YA8]PBVEUO``EM*)M2Ma,5CGAN<)' class TestClue3(unittest.TestCase): def test_bad_pass(self): soc = socket.socket(socket.AF_INET, socket.SOCK_STREAM) soc.connect((host, port)) soc.send("bad_pass") self.assertEqual(soc.recv(1000), "bad password") """ def test_pass_overflow(self): soc = socket.socket(socket.AF_INET, socket.SOCK_STREAM) soc.connect((host, port)) # ddoesn't actually overflow! thought 40k would do it. soc.send("a" * 100000) self.assertEqual(soc.recv(1000), "bad password") """ def test_no_pass_strobe_on(self): soc = socket.socket(socket.AF_INET, socket.SOCK_STREAM) soc.connect((host, port)) soc.send("strobe_on") self.assertEqual(soc.recv(1000), "bad password") def test_bad_pass_strobe_on(self): soc = socket.socket(socket.AF_INET, socket.SOCK_STREAM) soc.connect((host, port)) soc.send("aaaaa:strobe_on") self.assertEqual(soc.recv(1000), "bad password") def test_good_pass(self): soc = socket.socket(socket.AF_INET, socket.SOCK_STREAM) soc.connect((host, port)) soc.send(password) self.assertEqual(soc.recv(1000), "invalid request") def test_strobe_on(self): soc = socket.socket(socket.AF_INET, socket.SOCK_STREAM) soc.connect((host, port)) soc.send(password + " strobe_on") self.assertEqual(soc.recv(1000), "strobe on") time.sleep(3) # so we can see it def test_strobe_off(self): soc = socket.socket(socket.AF_INET, socket.SOCK_STREAM) soc.connect((host, port)) soc.send(password + " strobe_off") self.assertEqual(soc.recv(1000), "strobe off") def tearDown(self): soc = socket.socket(socket.AF_INET, socket.SOCK_STREAM) soc.connect((host, port)) soc.send(password + " strobe_off") self.assertEqual(soc.recv(1000), "strobe off") if __name__ == '__main__': unittest.main()

[ "matt@mattvenn.net" ]

matt@mattvenn.net

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/charles/Week 10/lab11/lab11_extra.py

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[]

no_license

charlesfrye/cs61a-summer2015

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1f5c0fbf5dce5d1322285595ca964493d9adbdfe

refs/heads/master

2016-08-07T06:06:09.335913

2015-08-21T00:33:25

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from lab11 import * ########### # Streams # ########### class Stream: class empty: def __repr__(self): return 'Stream.empty' empty = empty() def __init__(self, first, compute_rest=lambda: Stream.empty): assert callable(compute_rest), 'compute_rest must be callable.' self.first = first self._compute_rest = compute_rest @property def rest(self): """Return the rest of the stream, computing it if necessary.""" if self._compute_rest is not None: self._rest = self._compute_rest() self._compute_rest = None return self._rest def __repr__(self): return 'Stream({0}, <...>)'.format(repr(self.first)) def make_integer_stream(first=1): def compute_rest(): return make_integer_stream(first+1) return Stream(first, compute_rest) def add_streams(s1, s2): """Returns a stream that is the sum of s1 and s2. >>> stream1 = make_integer_stream() >>> stream2 = make_integer_stream(9) >>> added = add_streams(stream1, stream2) >>> added.first 10 >>> added.rest.first 12 >>> added.rest.rest.first 14 """ def compute_rest(): return add_streams(s1.rest,s2.rest) return Stream(s1.first+s2.first,compute_rest) def make_fib_stream(): """Return a stream containing the Fib sequence. >>> fib = make_fib_stream() >>> fib.first 0 >>> fib.rest.first 1 >>> fib.rest.rest.rest.rest.first 3 """ "*** YOUR CODE HERE ***" def compute_rest(): return add_streams(make_fib_stream(),make_fib_stream().rest) return Stream(0, lambda: Stream(1, compute_rest)) def filter_stream(filter_func, stream): def make_filtered_rest(): return filter_stream(filter_func, stream.rest) if stream == Stream.empty: return stream if filter_func(stream.first): return Stream(stream.first, make_filtered_rest) else: return filter_stream(filter_func, stream.rest) def interleave(stream1, stream2): """Return a stream with alternating values from stream1 and stream2. >>> ints = make_integer_stream(1) >>> fib = make_fib_stream() >>> alternating = interleave(ints, fib) >>> alternating.first 1 >>> alternating.rest.first 0 >>> alternating.rest.rest.first 2 >>> alternating.rest.rest.rest.first 1 """ def compute_rest(): return interleave(stream2,stream1.rest) if stream1 is Stream.empty: return stream1 else: return Stream(stream1.first,compute_rest)

[ "charlesfrye@berkeley.edu" ]

charlesfrye@berkeley.edu

c896ee7e54f79068157566d9203dc2d377ab2874

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[]

no_license

wsgan001/PyFPattern

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2023-08-25T23:48:26.112133

2021-10-23T14:11:22

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def run(self, tmp=None, task_vars=None): ' handler for fetch operations ' if (task_vars is None): task_vars = dict() result = super(ActionModule, self).run(tmp, task_vars) if self._play_context.check_mode: result['skipped'] = True result['msg'] = 'check mode not (yet) supported for this module' return result source = self._task.args.get('src', None) dest = self._task.args.get('dest', None) flat = boolean(self._task.args.get('flat')) fail_on_missing = boolean(self._task.args.get('fail_on_missing')) validate_checksum = boolean(self._task.args.get('validate_checksum', self._task.args.get('validate_md5'))) if (('validate_md5' in self._task.args) and ('validate_checksum' in self._task.args)): result['failed'] = True result['msg'] = 'validate_checksum and validate_md5 cannot both be specified' return result if ((source is None) or (dest is None)): result['failed'] = True result['msg'] = 'src and dest are required' return result source = self._connection._shell.join_path(source) source = self._remote_expand_user(source) remote_checksum = None if (not self._play_context.become): remote_checksum = self._remote_checksum(source, all_vars=task_vars, follow=True) remote_data = None if (remote_checksum in ('1', '2', None)): slurpres = self._execute_module(module_name='slurp', module_args=dict(src=source), task_vars=task_vars, tmp=tmp) if slurpres.get('failed'): if ((not fail_on_missing) and (slurpres.get('msg').startswith('file not found') or (remote_checksum == '1'))): result['msg'] = 'the remote file does not exist, not transferring, ignored' result['file'] = source result['changed'] = False else: result.update(slurpres) return result else: if (slurpres['encoding'] == 'base64'): remote_data = base64.b64decode(slurpres['content']) if (remote_data is not None): remote_checksum = checksum_s(remote_data) remote_source = slurpres.get('source') if (remote_source and (remote_source != source)): source = remote_source if (os.path.sep not in self._connection._shell.join_path('a', '')): source = self._connection._shell._unquote(source) source_local = source.replace('\\', '/') else: source_local = source dest = os.path.expanduser(dest) if flat: if dest.endswith(os.sep): base = os.path.basename(source_local) dest = os.path.join(dest, base) if (not dest.startswith('/')): dest = self._loader.path_dwim(dest) else: if ('inventory_hostname' in task_vars): target_name = task_vars['inventory_hostname'] else: target_name = self._play_context.remote_addr dest = ('%s/%s/%s' % (self._loader.path_dwim(dest), target_name, source_local)) dest = dest.replace('//', '/') if (remote_checksum in ('0', '1', '2', '3', '4')): result['changed'] = False result['file'] = source if (remote_checksum == '0'): result['msg'] = 'unable to calculate the checksum of the remote file' elif (remote_checksum == '1'): if fail_on_missing: result['failed'] = True del result['changed'] result['msg'] = 'the remote file does not exist' else: result['msg'] = 'the remote file does not exist, not transferring, ignored' elif (remote_checksum == '2'): result['msg'] = 'no read permission on remote file, not transferring, ignored' elif (remote_checksum == '3'): result['msg'] = 'remote file is a directory, fetch cannot work on directories' elif (remote_checksum == '4'): result['msg'] = "python isn't present on the system. Unable to compute checksum" return result local_checksum = checksum(dest) if (remote_checksum != local_checksum): makedirs_safe(os.path.dirname(dest)) if (remote_data is None): self._connection.fetch_file(source, dest) else: try: f = open(to_bytes(dest, errors='surrogate_or_strict'), 'wb') f.write(remote_data) f.close() except (IOError, OSError) as e: raise AnsibleError(('Failed to fetch the file: %s' % e)) new_checksum = secure_hash(dest) try: new_md5 = md5(dest) except ValueError: new_md5 = None if (validate_checksum and (new_checksum != remote_checksum)): result.update(dict(failed=True, md5sum=new_md5, msg='checksum mismatch', file=source, dest=dest, remote_md5sum=None, checksum=new_checksum, remote_checksum=remote_checksum)) else: result.update(dict(changed=True, md5sum=new_md5, dest=dest, remote_md5sum=None, checksum=new_checksum, remote_checksum=remote_checksum)) else: try: local_md5 = md5(dest) except ValueError: local_md5 = None result.update(dict(changed=False, md5sum=local_md5, file=source, dest=dest, checksum=local_checksum)) return result

[ "dg1732004@smail.nju.edu.cn" ]

dg1732004@smail.nju.edu.cn

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/scripts/validate_chicago_stkde.py

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gaberosser/crime-fighter

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__author__ = 'gabriel' import datetime import time import os import dill as pickle import logging import sys from pytz import utc from validation import validation, hotspot from kde import models as k_models from . import OUT_DIR, IN_DIR OUT_SUBDIR = 'validate_chicago_stkde' # global parameters num_sample_points = 30 grid_size = 150 # metres num_validation = 100 # number of predict - assess cycles start_date = datetime.datetime(2011, 3, 1) # first date for which data are required start_day_number = 366 # number of days (after start date) on which first prediction is made model_kwargs = { 'number_nn': 15, 'parallel': True, 'ncpu': 2, } ## DEBUGGING: #niter = 2 # number of SEPP iterations before convergence is assumed #num_validation = 2 # number of predict - assess cycles #num_sample_points = 2 # end_date is the maximum required date end_date = start_date + datetime.timedelta(days=start_day_number + num_validation) def run_me(data, data_index, domain, out_dir, run_name): log_file = os.path.join(out_dir, '%s.log' % run_name) if not os.path.isdir(out_dir): try: os.makedirs(out_dir) except OSError: # wait a moment, just in case another process has just done the folder creation time.sleep(1) if not os.path.isdir(out_dir): raise # set loggers logger = logging.getLogger(run_name) logger.setLevel(logging.DEBUG) fh = logging.FileHandler(log_file) formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') fh.setFormatter(formatter) logger.addHandler(fh) this_logger = logging.getLogger('validation.validation') this_logger.setLevel(logging.DEBUG) this_logger.handlers = [] # clear existing handlers this_logger.addHandler(fh) # replace with the same file output logger.info("Logger set. Script started.") # check that num_validation iterations is feasible if start_day_number + num_validation - 1 > data[-1, 0]: this_num_validation = int(data[-1, 0]) - start_day_number + 1 logger.info("Can only do %d validation runs" % this_num_validation) else: this_num_validation = num_validation logger.info("Instantiating validation object") hs = hotspot.STGaussianNn(**model_kwargs) vb = validation.ValidationIntegration(data, model=hs, data_index=data_index, spatial_domain=domain, cutoff_t=start_day_number) logger.info("Setting validation grid") vb.set_sample_units(grid_size, num_sample_points) file_stem = os.path.join(out_dir, run_name) try: logger.info("Starting validation run.") res = vb.run(time_step=1, n_iter=this_num_validation, verbose=True) except Exception as exc: logger.error(repr(exc)) res = None finally: logger.info("Saving results (or None).") with open(file_stem + '-validation.pickle', 'w') as f: pickle.dump(res, f) def main(region, crime_type): poly_file = os.path.join(IN_DIR, 'boundaries.pickle') with open(poly_file, 'r') as f: boundaries = pickle.load(f) domain = boundaries[region] data_infile = os.path.join(IN_DIR, 'chicago', region, '%s.pickle' % crime_type) with open(data_infile, 'r') as f: data, t0, cid = pickle.load(f) # cut data to selected date range sd = (start_date.replace(tzinfo=utc) - t0).days ed = (end_date.replace(tzinfo=utc) - t0).days data = data[(data[:, 0] >= sd) & (data[:, 0] < ed + 1)] data[:, 0] -= min(data[:, 0]) out_dir = os.path.join(OUT_DIR, OUT_SUBDIR, region, crime_type) run_name = '%s-%s' % (region, crime_type) run_me(data, cid, domain, out_dir, run_name) if __name__ == '__main__': assert len(sys.argv) == 3, "Two input arguments required" sys.exit(main(sys.argv[1], sys.argv[2]))

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#calss header class _SCENARIO(): def __init__(self,): self.name = "SCENARIO" self.definitions = [u'a description of possible actions or events in the future: ', u'a written plan of the characters and events in a play or film'] self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.specie = 'nouns' def run(self, obj1 = [], obj2 = []): return self.jsondata

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# The slug of the panel to be added to HORIZON_CONFIG. Required. PANEL = 'groups' # The slug of the dashboard the PANEL associated with. Required. PANEL_DASHBOARD = 'identity' # The slug of the panel group the PANEL is associated with. PANEL_GROUP = 'default' # Python panel class of the PANEL to be added. ADD_PANEL = 'openstack_dashboard.dashboards.identity.groups.panel.Groups' REMOVE_PANEL = True

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""" WSGI config for test_3719 project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/1.11/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault("DJANGO_SETTINGS_MODULE", "test_3719.settings") application = get_wsgi_application()

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#https://programmers.co.kr/learn/courses/30/lessons/17680 def solution(cacheSize, cities): answer = 0 cache = [] #캐시 for city in cities: # 도시 리스트를 순회 city = city.lower() # 소문자 변환 if city in cache: # 처리하려는 도시가 이미 캐시에 있으면 answer += 1 # cache hit, 1초 cache[cache.index(city)],cache[-1] = cache[-1], cache[cache.index(city)] # 캐시내의 사용된 데이터를 가장 마지막 인덱스로 옮긴다. else: answer += 5 # 캐시내에 없으면 5초 추가 if cacheSize > 0: # 캐시 사이즈가 0보다 크고 if len(cache) == cacheSize: # 캐시가 꽉차있다면 cache.pop(0) # 가장 사용 안된 데이터를 pop 해준다. cache.append(city) # 새로 들어온 데이터를 캐시에 넣어준다. else: # 사이즈에 여유가 있으면 cache.append(city) # 캐시에 넣어준다 return answer

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# Copyright 2011 OpenStack Foundation. # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import socket import uuid from oslo.config import cfg from barbican.openstack.common import context from barbican.openstack.common.gettextutils import _ # noqa from barbican.openstack.common import importutils from barbican.openstack.common import jsonutils from barbican.openstack.common import log as logging from barbican.openstack.common import timeutils LOG = logging.getLogger(__name__) notifier_opts = [ cfg.MultiStrOpt('notification_driver', default=[], help='Driver or drivers to handle sending notifications'), cfg.StrOpt('default_notification_level', default='INFO', help='Default notification level for outgoing notifications'), cfg.StrOpt('default_publisher_id', default=None, help='Default publisher_id for outgoing notifications'), ] CONF = cfg.CONF CONF.register_opts(notifier_opts) WARN = 'WARN' INFO = 'INFO' ERROR = 'ERROR' CRITICAL = 'CRITICAL' DEBUG = 'DEBUG' log_levels = (DEBUG, WARN, INFO, ERROR, CRITICAL) class BadPriorityException(Exception): pass def notify_decorator(name, fn): """Decorator for notify which is used from utils.monkey_patch(). :param name: name of the function :param function: - object of the function :returns: function -- decorated function """ def wrapped_func(*args, **kwarg): body = {} body['args'] = [] body['kwarg'] = {} for arg in args: body['args'].append(arg) for key in kwarg: body['kwarg'][key] = kwarg[key] ctxt = context.get_context_from_function_and_args(fn, args, kwarg) notify(ctxt, CONF.default_publisher_id or socket.gethostname(), name, CONF.default_notification_level, body) return fn(*args, **kwarg) return wrapped_func def publisher_id(service, host=None): if not host: try: host = CONF.host except AttributeError: host = CONF.default_publisher_id or socket.gethostname() return "%s.%s" % (service, host) def notify(context, publisher_id, event_type, priority, payload): """Sends a notification using the specified driver :param publisher_id: the source worker_type.host of the message :param event_type: the literal type of event (ex. Instance Creation) :param priority: patterned after the enumeration of Python logging levels in the set (DEBUG, WARN, INFO, ERROR, CRITICAL) :param payload: A python dictionary of attributes Outgoing message format includes the above parameters, and appends the following: message_id a UUID representing the id for this notification timestamp the GMT timestamp the notification was sent at The composite message will be constructed as a dictionary of the above attributes, which will then be sent via the transport mechanism defined by the driver. Message example:: {'message_id': str(uuid.uuid4()), 'publisher_id': 'compute.host1', 'timestamp': timeutils.utcnow(), 'priority': 'WARN', 'event_type': 'compute.create_instance', 'payload': {'instance_id': 12, ... }} """ if priority not in log_levels: raise BadPriorityException( _('%s not in valid priorities') % priority) # Ensure everything is JSON serializable. payload = jsonutils.to_primitive(payload, convert_instances=True) msg = dict(message_id=str(uuid.uuid4()), publisher_id=publisher_id, event_type=event_type, priority=priority, payload=payload, timestamp=str(timeutils.utcnow())) for driver in _get_drivers(): try: driver.notify(context, msg) except Exception as e: LOG.exception(_("Problem '%(e)s' attempting to " "send to notification system. " "Payload=%(payload)s") % dict(e=e, payload=payload)) _drivers = None def _get_drivers(): """Instantiate, cache, and return drivers based on the CONF.""" global _drivers if _drivers is None: _drivers = {} for notification_driver in CONF.notification_driver: try: driver = importutils.import_module(notification_driver) _drivers[notification_driver] = driver except ImportError: LOG.exception(_("Failed to load notifier %s. " "These notifications will not be sent.") % notification_driver) return _drivers.values() def _reset_drivers(): """Used by unit tests to reset the drivers.""" global _drivers _drivers = None

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from queue import Queue class Stack(Queue): def __init__(self): self.eq = Queue() self.dq = Queue() def push(self,item): self.eq.enqueue(item) def pop(self): if self.dq.size() == 0: while self.eq.size() > 0: self.dq.enqueue(self.eq.dequeue()) return self.dq.dequeue() def size(self): return self.dq.size() + self.eq.size() s = Stack() s.push(1) s.push(2) s.push(3) s.push(4) s.push(5) print "queue size=" print s.size() print s.eq.items, s.dq.items print s.pop() print s.eq.items, s.dq.items

[ "rayanki.kavitha@gmail.com" ]

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# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. 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 applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import pytest import torch from nemo.collections.tts.losses.audio_codec_loss import MaskedMAELoss, MaskedMSELoss class TestAudioCodecLoss: @pytest.mark.run_only_on('CPU') @pytest.mark.unit def test_masked_loss_l1(self): loss_fn = MaskedMAELoss() target = torch.tensor([[[1.0], [2.0], [0.0]], [[3.0], [0.0], [0.0]]]).transpose(1, 2) predicted = torch.tensor([[[0.5], [1.0], [0.0]], [[4.5], [0.0], [0.0]]]).transpose(1, 2) target_len = torch.tensor([2, 1]) loss = loss_fn(predicted=predicted, target=target, target_len=target_len) assert loss == 1.125 @pytest.mark.run_only_on('CPU') @pytest.mark.unit def test_masked_loss_l2(self): loss_fn = MaskedMSELoss() target = torch.tensor([[[1.0], [2.0], [4.0]], [[3.0], [0.0], [0.0]]]).transpose(1, 2) predicted = torch.tensor([[[0.5], [1.0], [4.0]], [[4.5], [0.0], [0.0]]]).transpose(1, 2) target_len = torch.tensor([3, 1]) loss = loss_fn(predicted=predicted, target=target, target_len=target_len) assert loss == (4 / 3)

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"""Representation of a single glyph including contour extraction""" from ttfquery import glyphquery import numpy class Glyph( object): """Object encapsulating metadata regarding a particular glyph""" def __init__(self, glyphName ): """Initialize the glyph object glyphName -- font's glyphName for this glyph, see glyphquery.glyphName() for extracting the appropriate name from character and encoding. """ self.glyphName = glyphName def compile( self, font, steps = 3 ): """Compile the glyph to a set of poly-line outlines""" self.contours = self.calculateContours( font ) self.outlines = [ decomposeOutline(contour,steps) for contour in self.contours ] self.width = glyphquery.width( font, self.glyphName ) self.height = glyphquery.lineHeight( font ) def calculateContours( self, font ): """Given a character, determine contours to draw returns a list of contours, with each contour being a list of ((x,y),flag) elements. There may be only a single contour. """ glyf = font['glyf'] charglyf = glyf[self.glyphName] return self._calculateContours( charglyf, glyf, font ) def _calculateContours( self, charglyf, glyf, font ): """Create expanded contour data-set from TTF charglyph entry This is called recursively for composite glyphs, so I suppose a badly-formed TTF file could cause an infinite loop. charglyph -- glyf table's entry for the target character glyf -- the glyf table (used for recursive calls) """ charglyf.expand( font ) # XXX is this extraneous? contours = [] if charglyf.numberOfContours == 0: # does not display at all, for instance, space pass elif charglyf.isComposite(): # composed out of other items... for component in charglyf.components: subContours = self._calculateContours( glyf[component.glyphName], glyf, font ) dx,dy = component.getComponentInfo()[1][-2:] # XXX we're ignoring the scaling/shearing/etceteras transformation # matrix which is given by component.getComponentInfo()[1][:4] subContours = [ [((x+dx,y+dy),f) for ((x,y),f) in subContour] for subContour in subContours ] contours.extend( subContours ) else: flags = charglyf.flags coordinates = charglyf.coordinates # We need to convert from the "end point" representation # to a distinct contour representation, requires slicing # each contour out of the list and then closing it last = 0 for e in charglyf.endPtsOfContours: set = zip( list(coordinates[last:e+1])+list(coordinates[last:last+1]), list(flags[last:e+1])+list(flags[last:last+1]) ) contours.append( list(set) ) last = e+1 if coordinates[last:]: contours.append( list(zip( list(coordinates[last:])+list(coordinates[last:last+1]), list(flags[last:])+list(flags[last:]) ) )) return contours def decomposeOutline( contour, steps=3 ): """Decompose a single TrueType contour to a line-loop In essence, this is the "interpretation" of the font as geometric primitives. I only support line and quadratic (conic) segments, which should support most TrueType fonts as far as I know. The process consists of first scanning for any multi- off-curve control-point runs. For each pair of such control points, we insert a new on-curve control point. Once we have the "expanded" control point array we scan through looking for each segment which includes an off-curve control point. These should only be bracketed by on-curve control points. For each found segment, we call our integrateQuadratic method to produce a set of points interpolating between the end points as affected by the middle control point. All other control points merely generate a single line-segment between the endpoints. """ # contours must be closed, but they can start with # (and even end with) items not on the contour... # so if we do, we need to create a new point to serve # as the midway... if len(contour)<3: return () set = contour[:] def on( record ): """Is this record on the contour? record = ((Ax,Ay),Af) """ return record[-1] == 1 def merge( first, second): """Merge two off-point records into an on-point record""" ((Ax,Ay),Af) = first ((Bx,By),Bf) = second return (((Ax+Bx)/2.0),((Ay+By))/2.0),1 # create an expanded set so that all adjacent # off-curve items have an on-curve item added # in between them last = contour[-1] expanded = [] for item in set: if (not on(item)) and (not on(last)): expanded.append( merge(last, item)) expanded.append( item ) last = item result = [] last = expanded[-1] while expanded: assert on(expanded[0]), "Expanded outline doesn't have proper format! Should always have either [on, off, on] or [on, on] as the first items in the outline" if len(expanded)>1: if on(expanded[1]): # line segment from 0 to 1 result.append( expanded[0][0] ) #result.append( expanded[1][0] ) del expanded[:1] else: if len(expanded) == 2: #KH assert on(expanded[0]), """Expanded outline finishes off-curve""" #KH result.append( expanded[1][0] ) #KH del expanded[:1] break assert on(expanded[2]), "Expanded outline doesn't have proper format!" points = integrateQuadratic( expanded[:3], steps = steps ) result.extend( points ) del expanded[:2] else: assert on(expanded[0]), """Expanded outline finishes off-curve""" result.append( expanded[0][0] ) del expanded[:1] result.append( result[-1] ) return result def integrateQuadratic( points, steps=3 ): """Get points on curve for quadratic w/ end points A and C Basis Equations are taken from here: http://www.truetype.demon.co.uk/ttoutln.htm This is a very crude approach to the integration, everything is coded directly in Python, with no attempts to speed up the process. XXX Should eventually provide adaptive steps so that the angle between the elements can determine how many steps are used. """ step = 1.0/steps ((Ax,Ay),_),((Bx,By),_),((Cx,Cy),_) = points result = [(Ax,Ay)] ### XXX This is dangerous, in certain cases floating point error ## can wind up creating a new point at 1.0-(some tiny number) if step ## is sliaghtly less than precisely 1.0/steps for t in numpy.arange( step, 1.0, step ): invT = 1.0-t px = (invT*invT * Ax) + (2*t*invT*Bx) + (t*t*Cx) py = (invT*invT * Ay) + (2*t*invT*By) + (t*t*Cy) result.append( (px,py) ) # the end-point will be added by the next segment... #result.append( (Cx,Cy) ) return result

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from jd.api.base import RestApi class KplOpenGetnewstockbyidQueryRequest(RestApi): def __init__(self,domain='gw.api.360buy.com',port=80): RestApi.__init__(self,domain, port) self.skuNums = None self.area = None def getapiname(self): return 'jd.kpl.open.getnewstockbyid.query'

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abhishekhbhootwala/py_amazfit_tools

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import logging from watchFaceParser.models.elements.common.iconSetElement import IconSetElement class PulseLinearElement(IconSetElement): # private static readonly Dictionary<DayOfWeek, int> DaysOfWeek = new Dictionary<DayOfWeek, int> # { # {DayOfWeek.Monday, 0}, # {DayOfWeek.Tuesday, 1}, # {DayOfWeek.Wednesday, 2}, # {DayOfWeek.Thursday, 3}, # {DayOfWeek.Friday, 4}, # {DayOfWeek.Saturday, 5}, # {DayOfWeek.Sunday, 6} # }; def __init__(self, parameter, parent, name = None): self._ar = [] #self._slices = 0 super(PulseLinearElement, self).__init__(parameter = parameter, parent = parent, name = name) def getCoordinatesArray(self): return self._ar def draw3(self, drawer, resources, state): assert(type(resources) == list) # pulse image does not overlap fakeZone = int(state.getPulse() * len(self._ar) / 200) x = self.getCoordinatesArray()[fakeZone]._x y = self.getCoordinatesArray()[fakeZone]._y temp = resources[self._imageIndex + fakeZone].getBitmap() drawer.paste(temp, (x,y), temp) def createChildForParameter(self, parameter): if parameter.getId() == 1: self._imageIndex = parameter.getValue() #print ("ARRAY",self._imageIndex) from watchFaceParser.models.elements.basic.valueElement import ValueElement return ValueElement(parameter, self, '?ImageIndex?') #print ( parameter.getValue(),parameter.getChildren()) elif parameter.getId() == 2: #print ( [ c.getValue() for c in parameter.getChildren()]) from watchFaceParser.models.elements.common.coordinatesElement import CoordinatesElement #print ( parameter.getValue(),parameter.getChildren()) #print (self.getName(),[c.getValue() for c in parameter.getChildren()]) #self._coordinates = [ CoordinatesElement(parameter = c, parent = self, name = 'CenterOffset') for c in parameter.getChildren()] #print (self._coordinates) self._coordinates = CoordinatesElement(parameter = parameter, parent = self, name = 'CenterOffset') self._ar.append(self._coordinates) #print (self._slices) #self._slices += 1 #return self._coordinates else: super(IconSetElement, self).createChildForParameter(parameter)

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gtalpo@gmail.com

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admiralbolt/gmhelper

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# Generated by Django 2.2.4 on 2019-09-02 14:45 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('panel', '0011_cityitem_name'), ] operations = [ migrations.AlterModelOptions( name='cityitem', options={'ordering': ['number']}, ), migrations.AddField( model_name='city', name='description', field=models.TextField(blank=True), ), ]

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/modules/image/classification/darknet53_imagenet/darknet.py

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# coding=utf-8 from __future__ import absolute_import from __future__ import division from __future__ import print_function import six import math from paddle import fluid from paddle.fluid.param_attr import ParamAttr from paddle.fluid.regularizer import L2Decay __all__ = ['DarkNet'] class DarkNet(object): """DarkNet, see https://pjreddie.com/darknet/yolo/ Args: depth (int): network depth, currently only darknet 53 is supported norm_type (str): normalization type, 'bn' and 'sync_bn' are supported norm_decay (float): weight decay for normalization layer weights get_prediction (bool): whether to get prediction class_dim (int): number of class while classification """ def __init__(self, depth=53, norm_type='sync_bn', norm_decay=0., weight_prefix_name='', get_prediction=False, class_dim=1000): assert depth in [53], "unsupported depth value" self.depth = depth self.norm_type = norm_type self.norm_decay = norm_decay self.depth_cfg = {53: ([1, 2, 8, 8, 4], self.basicblock)} self.prefix_name = weight_prefix_name self.class_dim = class_dim self.get_prediction = get_prediction def _conv_norm(self, input, ch_out, filter_size, stride, padding, act='leaky', name=None): conv = fluid.layers.conv2d( input=input, num_filters=ch_out, filter_size=filter_size, stride=stride, padding=padding, act=None, param_attr=ParamAttr(name=name + ".conv.weights"), bias_attr=False) bn_name = name + ".bn" bn_param_attr = ParamAttr(regularizer=L2Decay(float(self.norm_decay)), name=bn_name + '.scale') bn_bias_attr = ParamAttr(regularizer=L2Decay(float(self.norm_decay)), name=bn_name + '.offset') out = fluid.layers.batch_norm( input=conv, act=None, param_attr=bn_param_attr, bias_attr=bn_bias_attr, moving_mean_name=bn_name + '.mean', moving_variance_name=bn_name + '.var') # leaky relu here has `alpha` as 0.1, can not be set by # `act` param in fluid.layers.batch_norm above. if act == 'leaky': out = fluid.layers.leaky_relu(x=out, alpha=0.1) return out def _downsample(self, input, ch_out, filter_size=3, stride=2, padding=1, name=None): return self._conv_norm(input, ch_out=ch_out, filter_size=filter_size, stride=stride, padding=padding, name=name) def basicblock(self, input, ch_out, name=None): conv1 = self._conv_norm(input, ch_out=ch_out, filter_size=1, stride=1, padding=0, name=name + ".0") conv2 = self._conv_norm(conv1, ch_out=ch_out * 2, filter_size=3, stride=1, padding=1, name=name + ".1") out = fluid.layers.elementwise_add(x=input, y=conv2, act=None) return out def layer_warp(self, block_func, input, ch_out, count, name=None): out = block_func(input, ch_out=ch_out, name='{}.0'.format(name)) for j in six.moves.xrange(1, count): out = block_func(out, ch_out=ch_out, name='{}.{}'.format(name, j)) return out def __call__(self, input): """Get the backbone of DarkNet, that is output for the 5 stages. :param input: Variable of input image :type input: Variable :Returns: The last variables of each stage. """ stages, block_func = self.depth_cfg[self.depth] stages = stages[0:5] conv = self._conv_norm( input=input, ch_out=32, filter_size=3, stride=1, padding=1, name=self.prefix_name + "yolo_input") downsample_ = self._downsample( input=conv, ch_out=conv.shape[1] * 2, name=self.prefix_name + "yolo_input.downsample") blocks = [] for i, stage in enumerate(stages): block = self.layer_warp( block_func=block_func, input=downsample_, ch_out=32 * 2**i, count=stage, name=self.prefix_name + "stage.{}".format(i)) blocks.append(block) if i < len(stages) - 1: # do not downsaple in the last stage downsample_ = self._downsample( input=block, ch_out=block.shape[1] * 2, name=self.prefix_name + "stage.{}.downsample".format(i)) if self.get_prediction: pool = fluid.layers.pool2d(input=block, pool_type='avg', global_pooling=True) stdv = 1.0 / math.sqrt(pool.shape[1] * 1.0) out = fluid.layers.fc( input=pool, size=self.class_dim, param_attr=ParamAttr(initializer=fluid.initializer.Uniform(-stdv, stdv), name='fc_weights'), bias_attr=ParamAttr(name='fc_offset')) out = fluid.layers.softmax(out) return out else: return blocks

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wuzewu@baidu.com

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/untitled6/testvideo/views.py

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alingb/PycharmProjects

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refs/heads/master

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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.shortcuts import render # Create your views here. from django.templatetags.static import register from django.utils.safestring import mark_safe from testvideo import models @register.simple_tag def action_all(current_url, index): """ 获取当前url，video-1-1-2.html :param current_url: :param item: :return: """ url_part_list = current_url.split('-') if index == 3: if url_part_list[index] == "0.html": temp = "<a href='%s' class='active'>全部</a>" else: temp = "<a href='%s'>全部</a>" url_part_list[index] = "0.html" else: if url_part_list[index] == "0": temp = "<a href='%s' class='active'>全部</a>" else: temp = "<a href='%s'>全部</a>" url_part_list[index] = "0" href = '-'.join(url_part_list) temp = temp % (href,) return mark_safe(temp) @register.simple_tag def action(current_url, item, index): # videos-0-0-1.html # item: id name # video- 2 -0-0.html url_part_list = current_url.split('-') if index == 3: if str(item['id']) == url_part_list[3].split('.')[0]: # 如果当前标签被选中 temp = "<a href='%s' class='active'>%s</a>" else: temp = "<a href='%s'>%s</a>" url_part_list[index] = str(item['id']) + '.html' # 拼接对应位置的部分url else: if str(item['id']) == url_part_list[index]: temp = "<a href='%s' class='active'>%s</a>" else: temp = "<a href='%s'>%s</a>" url_part_list[index] = str(item['id']) ur_str = '-'.join(url_part_list) # 拼接整体url temp = temp % (ur_str, item['name']) # 生成对应的a标签 return mark_safe(temp) # 返回安全的html def video(request,*args,**kwargs): print(kwargs) # 当前请求的路径 request_path = request.path # 从数据库获取视频时的filter条件字典 q = {} # 状态为审核通过的 q['status'] = 1 # 获取url中的视频分类id class_id = int(kwargs.get('classification_id')) # 从数据库中获取所有的视频方向（包括视频方向的id和name） direction_list = models.Direction.objects.all().values('id','name') # 如果视频方向是0 if kwargs.get('direction_id') == '0': # 方向选择全部 # 方向id=0，即获取所有的视频分类（包括视频分类的id和name） class_list = models.Classification.objects.all().values('id', 'name') # 如果视频分类id也为0，即全部分类，那就什么都不用做，因为已经全取出来了 if kwargs.get('classification_id') == '0': pass else: # 如果视频分类不是全部，过滤条件为视频分类id在[url中的视频分类id] q['classification_id__in'] = [class_id,] else: print('方向不为0') # 方向选择某一个方向， # 如果分类是0 if kwargs.get('classification_id') == '0': print('分类为0') # 获取已选择的视频方向 obj = models.Direction.objects.get(id=int(kwargs.get('direction_id'))) # 获取该方向的所有视频分类 class_list = obj.classification.all().values('id', 'name') # 获取所有视频分类对应的视频分类id id_list = list(map(lambda x: x['id'], class_list)) # 过滤条件为视频分类id in [该方向下的所有视频分类id] q['classification_id__in'] = id_list else: # 方向不为0，分类也不为0 obj = models.Direction.objects.get(id=int(kwargs.get('direction_id'))) class_list = obj.classification.all().values('id', 'name') id_list = list(map(lambda x:x['id'], class_list)) # 过滤条件为视频分类id in [已经选择的视频分类id] q['classification_id__in'] = [class_id,] print('分类不为0') # 当前分类如果在获取的所有分类中，则方向下的所有相关分类显示 # 当前分类如果不在获取的所有分类中， if int(kwargs.get('classification_id')) in id_list: pass else: print('不再,获取指定方向下的所有分类：选中的回到全部') url_part_list = request_path.split('-') url_part_list[2] = '0' request_path = '-'.join(url_part_list) # 视频等级id level_id = int(kwargs.get('level_id')) if level_id == 0: pass else: # 过滤条件增加视频等级 q['level'] = level_id # 取出相对应的视频 video_list = models.Video.objects.filter(**q).values('title','summary', 'img', 'href') # 把视频等级转化为单个标签是字典格式，整体是列表格式 ret = map(lambda x:{"id": x[0], 'name': x[1]}, models.Video.level_choice) level_list = list(ret) return render(request, 'video.html', {'direction_list': direction_list, 'class_list': class_list, 'level_list': level_list, 'current_url': request_path, "video_list": video_list})

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from typing import Optional, Tuple import torch import torch.nn as nn from torch.fx import GraphModule from transformers.pytorch_utils import Conv1D from colossalai._analyzer.fx.graph_module import ColoGraphModule from colossalai._analyzer.fx.passes import shape_prop_pass # from colossalai.fx.tracer.tracer import ColoTracer from colossalai._analyzer.fx.tracer.tracer import ColoTracer from colossalai.auto_parallel.tensor_shard.utils.factory import find_repeat_blocks from colossalai.testing import clear_cache_before_run, parameterize, run_on_environment_flag NUM_REPEAT_BLOCKS = 4 BATCH_SIZE = 1 SEQ_LENGTH = 32 HIDDEN_DIM = 384 class RepeatBlock(nn.Module): def __init__(self, intermediate_size, hidden_size): super().__init__() self.c_fc = Conv1D(intermediate_size, hidden_size) self.c_proj = Conv1D(hidden_size, intermediate_size) self.act = torch.nn.ReLU() def forward(self, hidden_states: Optional[Tuple[torch.FloatTensor]]) -> torch.FloatTensor: hidden_states = self.c_fc(hidden_states) hidden_states = self.act(hidden_states) hidden_states = self.c_proj(hidden_states) return hidden_states class RepeatModel(nn.Module): def __init__(self, intermediate_size, hidden_size, num_layers): super().__init__() self.blocks = nn.ModuleList([RepeatBlock(intermediate_size, hidden_size) for i in range(num_layers)]) def forward(self, x): for block in self.blocks: x = block(x) return x class NonRepeatBlock(nn.Module): def __init__(self, intermediate_size, hidden_size, layer_index): super().__init__() intermediate_size //= (layer_index + 1) self.c_fc = Conv1D(intermediate_size, hidden_size) self.c_proj = Conv1D(hidden_size, intermediate_size) self.act = torch.nn.ReLU() def forward(self, hidden_states: Optional[Tuple[torch.FloatTensor]]) -> torch.FloatTensor: hidden_states = self.c_fc(hidden_states) hidden_states = self.act(hidden_states) hidden_states = self.c_proj(hidden_states) return hidden_states class NonRepeatModel(nn.Module): def __init__(self, intermediate_size, hidden_size, num_layers): super().__init__() self.blocks = nn.ModuleList([NonRepeatBlock(intermediate_size, hidden_size, i) for i in range(num_layers)]) def forward(self, x): for block in self.blocks: x = block(x) return x @run_on_environment_flag(name='AUTO_PARALLEL') @clear_cache_before_run() @parameterize('model_cls', [RepeatModel, NonRepeatModel]) def test_repeat_blocks(model_cls): model = model_cls(4 * HIDDEN_DIM, HIDDEN_DIM, NUM_REPEAT_BLOCKS) tracer = ColoTracer(bias_addition_split=True) input_sample = {'x': torch.rand(BATCH_SIZE, SEQ_LENGTH, HIDDEN_DIM).to('meta')} graph = tracer.trace(root=model, meta_args=input_sample) gm = GraphModule(model, graph, model.__class__.__name__) shape_prop_pass(gm, *input_sample.values()) gm.recompile() node_list = list(graph.nodes) root_module = graph.owning_module common_blocks = find_repeat_blocks(node_list, root_module, common_length_threshold=10) total_num_nodes = len(list(graph.nodes)) # remove the input placeholder node and the output node num_repeat_nodes_per_block = (total_num_nodes - 2) // NUM_REPEAT_BLOCKS for common_block in common_blocks: print(common_block) if model_cls == RepeatModel: assert len(common_blocks) == NUM_REPEAT_BLOCKS assert len(common_blocks[0]) == num_repeat_nodes_per_block elif model_cls == NonRepeatModel: assert len(common_blocks) == 0 if __name__ == '__main__': test_repeat_blocks()

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import threading print("Welcome") class test(threading.Thread): def run(self): for i in range(5): print("hey") t1=test() t1.run() for j in range(5): print("hello") """ Welcome hey hey hey hey hey hello hello hello hello hello in this above example we are creating a thread but it is not activated """

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#space complexity(O(1)) class Solution: def gameOfLife(self, board: List[List[int]]) -> None: m=len(board) n=len(board[0]) def isValidNeighbor(x, y): return x < len(board) and x >= 0 and y < len(board[0]) and y >= 0 # All directions of neighbors x_dir = [-1, -1, -1, 0, 0, 1, 1, 1] y_dir = [-1, 0, 1, -1,1,-1, 0, 1] for row in range(0,m): for col in range(0,n): live_neighbors = 0 for i in range(8): curr_x, curr_y = row + x_dir[i], col + y_dir[i] if isValidNeighbor(curr_x, curr_y) and abs(board[curr_x][curr_y]) == 1: live_neighbors+=1 # Rules 1 and 3: -1 indicates a cell that was live but now is dead. if board[row][col] == 1 and (live_neighbors < 2 or live_neighbors > 3): board[row][col] = -1 # Rule 4: 2 indicates a cell that was dead but now is live. if board[row][col] == 0 and live_neighbors == 3: board[row][col] = 2 # Get the final board for row in range(len(board)): for col in range(len(board[0])): if board[row][col] >= 1: board[row][col] = 1 else: board[row][col] = 0

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""" *Upper-West 5* |⠟| The upper-west five gi. """ from dataclasses import dataclass from kagi import Kagi from ..._gi import StrismicGi from ...west import WesternGi from ..._number import FiveGi from .._gi import UpperGi __all__ = ["UpperWest5"] @dataclass class UpperWest5( Gi, StrismicGi, UpperGi, WesternGi, FiveGi, ): symbol = "\u281f"

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import logging from django.core.exceptions import ValidationError from dojo.models import Product_API_Scan_Configuration from .api_client import CobaltAPI logger = logging.getLogger(__name__) class CobaltApiImporter(object): """ Import from Cobalt.io API """ def get_findings(self, test): client, config = self.prepare_client(test) findings = client.get_findings(config.service_key_1) return findings def prepare_client(self, test): product = test.engagement.product if test.api_scan_configuration: config = test.api_scan_configuration # Double check of config if config.product != product: raise ValidationError( "API Scan Configuration for Cobalt.io and Product do not match. " f'Product: "{product.name}" ({product.id}), config.product: "{config.product.name}" ({config.product.id})' ) else: configs = Product_API_Scan_Configuration.objects.filter( product=product, tool_configuration__tool_type__name="Cobalt.io", ) if configs.count() == 1: config = configs.first() elif configs.count() > 1: raise ValidationError( "More than one Product API Scan Configuration has been configured, but none of them has been " "chosen. Please specify at Test which one should be used. " f'Product: "{product.name}" ({product.id})' ) else: raise ValidationError( "There are no API Scan Configurations for this Product. Please add at least one API Scan " "Configuration for Cobalt.io to this Product. " f'Product: "{product.name}" ({product.id})' ) tool_config = config.tool_configuration return CobaltAPI(tool_config), config

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#calss header class _MOOTING(): def __init__(self,): self.name = "MOOTING" self.definitions = moot self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.basic = ['moot']

[ "xingwang1991@gmail.com" ]

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import sys sys.stdin = open('input_data/2628.txt','r') # 정보 주워담기 width, height = list(map(int,input().split())) cutting = int(input()) cuttings = [] verti = [width] hori = [height] for _ in range(cutting): cuttings.append(list(map(int,input().split()))) #가로 / 세로 분류하기 for cut in cuttings: if cut[0] == 0: hori.append(cut[1]) else: verti.append(cut[1]) # 분류한거 순서대로 분류하기 verti.sort() hori.sort() verti_len = len(verti) hori_len = len(hori) # 자른 선 크기별로 구분하기 verti_paper,hori_paper = [0] * verti_len, [0] * hori_len hori_paper[0], verti_paper[0] = hori[0], verti[0] for i in range(1,verti_len): verti_paper[i] = verti[i]-verti[i-1] for i in range(1, hori_len): hori_paper[i] = hori[i] - hori[i - 1] # 크기 구하기 result = [] for i in hori_paper: for j in verti_paper: result.append(i*j) print(max(result)) # 4,10 --> 4,6 # 2,3,8 --> 2 ,1 5

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from output.models.sun_data.elem_decl.value_constraint.value_constraint01001m.value_constraint01001m4_xsd.value_constraint01001m4 import ( Id, Root, ) __all__ = [ "Id", "Root", ]

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2014-01-14T19:33:27

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from setuptools import setup, find_packages tolines = lambda c: filter(None, map(lambda s: s.strip(), c.split('\n'))) def read(filename, flt=None): with open(filename) as f: content = f.read().strip() return flt(content) if callable(flt) else content def requirements_filter(c): install_requires = [] for requirement in tolines(c): _pound_pos = requirement.find('#') if _pound_pos != -1: requirement = requirement[0:_pound_pos].strip() if len(requirement): install_requires.append(requirement) return install_requires version = read('version.txt') setup( name='rdc.dic', namespace_packages = ['rdc'], version=version, description="Simple dependency injection container", long_description=read('README.rst'), classifiers=read('classifiers.txt', tolines), author='Romain Dorgueil', author_email='romain@dorgueil.net', url='http://dic.rdc.li/', download_url='https://github.com/rdcli/rdc.dic/tarball/' + version, license='Apache License, Version 2.0', packages=find_packages(exclude=['ez_setup', 'example', 'test']), include_package_data=True, install_requires=read('requirements.txt', requirements_filter), )

[ "romain@dorgueil.net" ]

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[]

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nimadorostkar/simpleCRM

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#!/Users/nima/github/AtroCRM/env/bin/python3 # -*- coding: utf-8 -*- import re import sys from pip._internal.cli.main import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit(main())

[ "nimadorostkar97@gmail.com" ]

nimadorostkar97@gmail.com

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/src/datasets/cifar10.py

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luzai/few-shot

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2017-11-22T08:32:36

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# Copyright 2016 The TensorFlow 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 applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Provides data for the Cifar10 dataset. The dataset scripts used to create the dataset can be found at: tensorflow/models/slim/datasets/download_and_convert_cifar10.py """ from __future__ import division from __future__ import absolute_import import os import tensorflow as tf from datasets import dataset_utils from preprocessing import cifar_preprocessing slim = tf.contrib.slim _FILE_PATTERN = 'cifar10_%s.tfrecord' SPLITS_TO_SIZES = {'train': 50000, 'test': 10000} _NUM_CLASSES = 10 _ITEMS_TO_DESCRIPTIONS = { 'image': 'A [32 x 32 x 3] color image.', 'label': 'A single integer between 0 and 9', } def load_batch(dataset, batch_size, height=32, width=32, is_training=False): data_provider = slim.dataset_data_provider.DatasetDataProvider( dataset, num_readers=8, common_queue_capacity=40 * batch_size, common_queue_min=20 * batch_size) image, label = data_provider.get(['image', 'label']) image = cifar_preprocessing.preprocess_image( image, height, width, is_training,label=label) images, labels = tf.train.batch( [image, label], batch_size=batch_size, # allow_smaller_final_batch=True, num_threads=8, capacity=30 * batch_size, ) batch_queue = slim.prefetch_queue.prefetch_queue( [images, labels], num_threads=512, capacity=10 * batch_size, name='prefetch/train' if is_training else 'prefetch/val' ) return batch_queue def get_split(split_name, dataset_dir, file_pattern=None, reader=None): """Gets a dataset tuple with instructions for reading cifar10. Args: split_name: A train/test split name. dataset_dir: The base directory of the dataset sources. file_pattern: The file pattern to use when matching the dataset sources. It is assumed that the pattern contains a '%s' string so that the split name can be inserted. reader: The TensorFlow reader type. Returns: A `Dataset` namedtuple. Raises: ValueError: if `split_name` is not a valid train/test split. """ if split_name not in SPLITS_TO_SIZES: raise ValueError('split name %s was not recognized.' % split_name) if not file_pattern: file_pattern = _FILE_PATTERN file_pattern = os.path.join(dataset_dir, file_pattern % split_name) # Allowing None in the signature so that dataset_factory can use the default. if not reader: reader = tf.TFRecordReader keys_to_features = { 'image/encoded': tf.FixedLenFeature((), tf.string, default_value=''), 'image/format': tf.FixedLenFeature((), tf.string, default_value='png'), 'image/class/label': tf.FixedLenFeature( [], tf.int64, default_value=tf.zeros([], dtype=tf.int64)), } items_to_handlers = { 'image': slim.tfexample_decoder.Image(shape=[32, 32, 3]), 'label': slim.tfexample_decoder.Tensor('image/class/label'), } decoder = slim.tfexample_decoder.TFExampleDecoder( keys_to_features, items_to_handlers) labels_to_names = None if dataset_utils.has_labels(dataset_dir): labels_to_names = dataset_utils.read_label_file(dataset_dir) return slim.dataset.Dataset( data_sources=file_pattern, reader=reader, decoder=decoder, num_samples=SPLITS_TO_SIZES[split_name], items_to_descriptions=_ITEMS_TO_DESCRIPTIONS, num_classes=_NUM_CLASSES, labels_to_names=labels_to_names)

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907682447@qq.com

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/pardus/tags/2007.1/server/database/mysql/actions.py

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[]

no_license

aligulle1/kuller

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#!/usr/bin/python # -*- coding: utf-8 -*- # # Copyright 2005 TUBITAK/UEKAE # Licensed under the GNU General Public License, version 2. # See the file http://www.gnu.org/copyleft/gpl.txt. from pisi.actionsapi import autotools from pisi.actionsapi import libtools from pisi.actionsapi import pisitools from pisi.actionsapi import shelltools from pisi.actionsapi import get def setup(): # Don't use zlib from source pisitools.dosed("configure.in", "zlib/Makefile dnl", "dnl zlib/Makefile") # Plain autoconf doesn't work here... shelltools.export("WANT_AUTOCONF", "2.59") autotools.autoreconf("--force") libtools.libtoolize("--copy --force") libtools.gnuconfig_update() shelltools.cd("innobase/") autotools.autoreconf("--force") libtools.libtoolize("--copy --force") libtools.gnuconfig_update() shelltools.cd("../") # Export flags shelltools.export("CFLAGS", "%s -DHAVE_ERRNO_AS_DEFINE=1" % get.CFLAGS()) shelltools.export("CXXFLAGS", "%s \ -felide-constructors \ -fno-exceptions \ -fno-rtti \ -fno-implicit-templates" % get.CXXFLAGS()) # Configure! autotools.configure("--libexecdir=/usr/sbin \ --sysconfdir=/etc/mysql \ --localstatedir=/var/lib/mysql \ --with-low-memory \ --enable-local-infile \ --with-mysqld-user=mysql \ --with-client-ldflags=-lstdc++ \ --enable-thread-safe-client \ --with-comment=\"Pardus Linux\" \ --with-unix-socket-path=/var/run/mysqld/mysqld.sock \ --with-lib-ccflags=\"-fPIC\" \ --with-readline \ --without-docs \ --enable-shared \ --disable-static \ --without-libwrap \ --with-openssl \ --without-debug \ --with-charset=utf8 \ --with-collation=utf8_general_ci \ --with-extra-charsets=all \ --with-berkeley-db=./bdb \ --with-geometry \ --with-big-tables \ --without-bench \ --with-max-indexes=128 \ --enable-assembler") def build(): autotools.make() def install(): autotools.rawInstall("DESTDIR=%s benchdir_root=\"/usr/share/mysql\"" % get.installDIR()) # Extra headers pisitools.insinto("/usr/include/mysql", "include/my_config.h") pisitools.insinto("/usr/include/mysql", "include/my_dir.h") # Links pisitools.dosym("mysqlcheck", "/usr/bin/mysqlanalyze") pisitools.dosym("mysqlcheck", "/usr/bin/mysqlrepair") pisitools.dosym("mysqlcheck", "/usr/bin/mysqloptimize") # Cleanup pisitools.remove("/usr/bin/make*distribution") pisitools.remove("/usr/share/mysql/make_*_distribution") pisitools.remove("/usr/share/mysql/mysql.server") pisitools.remove("/usr/share/mysql/binary-configur") pisitools.remove("/usr/share/mysql/mysql-log-rotate") pisitools.remove("/usr/share/mysql/postinstall") pisitools.remove("/usr/share/mysql/preinstall") pisitools.remove("/usr/share/mysql/mi_test*") pisitools.remove("/usr/share/mysql/*.spec") pisitools.remove("/usr/share/mysql/*.plist") pisitools.remove("/usr/share/mysql/my-*.cnf") # Move libs to /usr/lib pisitools.domove("/usr/lib/mysql/libmysqlclient*.so*", "/usr/lib") # Links to libs pisitools.dosym("../libmysqlclient.so", "/usr/lib/mysql/libmysqlclient.so") pisitools.dosym("../libmysqlclient_r.so", "/usr/lib/mysql/libmysqlclient_r.so") # No perl for i in ["mysqlhotcopy", "mysql_find_rows", "mysql_convert_table_format", "mysqld_multi", "mysqlaccess", "mysql_fix_extensions", "mysqldumpslow", "mysql_zap", "mysql_explain_log", "mysql_tableinfo", "mysql_setpermission"]: pisitools.remove("/usr/bin/%s" % i) # No tests pisitools.removeDir("/usr/share/mysql/mysql-test") # Config pisitools.insinto("/etc/mysql", "scripts/mysqlaccess.conf") # Data dir pisitools.dodir("/var/lib/mysql") # Logs pisitools.dodir("/var/log/mysql") shelltools.touch("%s/var/log/mysql/mysql.log" % get.installDIR()) shelltools.touch("%s/var/log/mysql/mysql.err" % get.installDIR()) # Runtime data pisitools.dodir("/var/run/mysqld") # Documents pisitools.dodoc("README", "COPYING", "ChangeLog", "EXCEPTIONS-CLIENT", "INSTALL-SOURCE") pisitools.dohtml("Docs/*.html") pisitools.dodoc("Docs/manual.txt," "Docs/manual.ps") pisitools.dodoc("support-files/my-*.cnf")

[ "yusuf.aydemir@istanbul.com" ]

yusuf.aydemir@istanbul.com

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/kiwibackend/application/website/messages/http/smallGameFinish_request.py

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whiteprism/mywork

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# -*- encoding:utf8 -*- from messages.http import BaseHttp class SmallGameFinishRequest(BaseHttp): def __init__(self): super(self.__class__, self).__init__() self.score = -1

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snoster@163.com

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no_license

CourAgeZ/MachineLearning

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import numpy as np from math import pi from Util.Timing import Timing from Util.Bases import ClassifierBase from Util.Metas import ClassifierMeta sqrt_pi = (2 * pi) ** 0.5 class NBFunctions: @staticmethod def gaussian(x, mu, sigma): return np.exp(-(x - mu) ** 2 / (2 * sigma ** 2)) / (sqrt_pi * sigma) @staticmethod def gaussian_maximum_likelihood(labelled_x, n_category, dim): mu = [np.sum( labelled_x[c][dim]) / len(labelled_x[c][dim]) for c in range(n_category)] sigma = [np.sum( (labelled_x[c][dim] - mu[c]) ** 2) / len(labelled_x[c][dim]) for c in range(n_category)] def func(_c): def sub(_x): return NBFunctions.gaussian(_x, mu[_c], sigma[_c]) return sub return [func(_c=c) for c in range(n_category)] class NaiveBayes(ClassifierBase, metaclass=ClassifierMeta): NaiveBayesTiming = Timing() def __init__(self): self._x = self._y = None self._data = self._func = None self._n_possibilities = None self._labelled_x = self._label_zip = None self._cat_counter = self._con_counter = None self.label_dic = self._feat_dics = None def feed_data(self, x, y, sample_weight=None): pass def _feed_sample_weight(self, sample_weight=None): pass @NaiveBayesTiming.timeit(level=2, prefix="[API] ") def get_prior_probability(self, lb=1): return [(_c_num + lb) / (len(self._y) + lb * len(self._cat_counter)) for _c_num in self._cat_counter] @NaiveBayesTiming.timeit(level=2, prefix="[API] ") def fit(self, x=None, y=None, sample_weight=None, lb=1): if x is not None and y is not None: self.feed_data(x, y, sample_weight) self._func = self._fit(lb) def _fit(self, lb): pass @NaiveBayesTiming.timeit(level=1, prefix="[API] ") def predict(self, x, get_raw_result=False): if isinstance(x, np.ndarray): x = x.tolist() else: x = [xx[:] for xx in x] x = self._transfer_x(x) m_arg, m_probability = np.zeros(len(x), dtype=np.int8), np.zeros(len(x)) for i in range(len(self._cat_counter)): p = self._func(x, i) _mask = p > m_probability m_arg[_mask], m_probability[_mask] = i, p[_mask] if not get_raw_result: return np.array([self.label_dic[arg] for arg in m_arg]) return m_probability def _transfer_x(self, x): return x

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# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union from ... import _utilities, _tables __all__ = [ 'GetPolicyAssignmentResult', 'AwaitableGetPolicyAssignmentResult', 'get_policy_assignment', ] @pulumi.output_type class GetPolicyAssignmentResult: """ The policy assignment. """ def __init__(__self__, display_name=None, name=None, policy_definition_id=None, scope=None, type=None): if display_name and not isinstance(display_name, str): raise TypeError("Expected argument 'display_name' to be a str") pulumi.set(__self__, "display_name", display_name) if name and not isinstance(name, str): raise TypeError("Expected argument 'name' to be a str") pulumi.set(__self__, "name", name) if policy_definition_id and not isinstance(policy_definition_id, str): raise TypeError("Expected argument 'policy_definition_id' to be a str") pulumi.set(__self__, "policy_definition_id", policy_definition_id) if scope and not isinstance(scope, str): raise TypeError("Expected argument 'scope' to be a str") pulumi.set(__self__, "scope", scope) if type and not isinstance(type, str): raise TypeError("Expected argument 'type' to be a str") pulumi.set(__self__, "type", type) @property @pulumi.getter(name="displayName") def display_name(self) -> Optional[str]: """ The display name of the policy assignment. """ return pulumi.get(self, "display_name") @property @pulumi.getter def name(self) -> Optional[str]: """ The name of the policy assignment. """ return pulumi.get(self, "name") @property @pulumi.getter(name="policyDefinitionId") def policy_definition_id(self) -> Optional[str]: """ The ID of the policy definition. """ return pulumi.get(self, "policy_definition_id") @property @pulumi.getter def scope(self) -> Optional[str]: """ The scope for the policy assignment. """ return pulumi.get(self, "scope") @property @pulumi.getter def type(self) -> Optional[str]: """ The type of the policy assignment. """ return pulumi.get(self, "type") class AwaitableGetPolicyAssignmentResult(GetPolicyAssignmentResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetPolicyAssignmentResult( display_name=self.display_name, name=self.name, policy_definition_id=self.policy_definition_id, scope=self.scope, type=self.type) def get_policy_assignment(policy_assignment_name: Optional[str] = None, scope: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetPolicyAssignmentResult: """ Use this data source to access information about an existing resource. :param str policy_assignment_name: The name of the policy assignment to get. :param str scope: The scope of the policy assignment. """ __args__ = dict() __args__['policyAssignmentName'] = policy_assignment_name __args__['scope'] = scope if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-nextgen:authorization/v20160401:getPolicyAssignment', __args__, opts=opts, typ=GetPolicyAssignmentResult).value return AwaitableGetPolicyAssignmentResult( display_name=__ret__.display_name, name=__ret__.name, policy_definition_id=__ret__.policy_definition_id, scope=__ret__.scope, type=__ret__.type)

[ "public@paulstack.co.uk" ]

public@paulstack.co.uk

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/third_party/onnx-tensorrt/third_party/onnx/onnx/backend/test/case/node/greater.py

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kurff/pytorch

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from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np # type: ignore import onnx from ..base import Base from . import expect class Greater(Base): @staticmethod def export(): node = onnx.helper.make_node( 'Greater', inputs=['x', 'y'], outputs=['greater'], ) x = np.random.randn(3, 4, 5).astype(np.float32) y = np.random.randn(3, 4, 5).astype(np.float32) z = np.greater(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_greater') @staticmethod def export_greater_broadcast(): node = onnx.helper.make_node( 'Greater', inputs=['x', 'y'], outputs=['greater'], broadcast=1, ) x = np.random.randn(3, 4, 5).astype(np.float32) y = np.random.randn(5).astype(np.float32) z = np.greater(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_greater_bcast')

[ "kurffzhou@tencent.com" ]

kurffzhou@tencent.com

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/tests/test_bind.py

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TrendingTechnology/typical

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from __future__ import annotations import inspect import pytest import typic def foo(arg, *args, kwd=None, **kwargs): # pragma: nocover pass def one(arg): # pragma: nocover pass def pos(arg, *args): # pragma: nocover pass def kwd(*, kwd=None): # pragma: nocover pass def kwarg(arg, **kwargs): # pragma: nocover pass def typed(arg: str): # pragma: nocover return type(arg) def test_bind(): sig = inspect.signature(foo) args, kwargs = (1, 2), {"kwd": "kwd", "kwarg": "kwarg"} builtin: inspect.BoundArguments = sig.bind(*args, **kwargs) baked = typic.bind(foo, *args, **kwargs) assert builtin.kwargs == baked.kwargs assert builtin.args == baked.args assert dict(builtin.arguments) == baked.arguments def test_typed_no_coerce(): bound = typic.bind(typed, 1, coerce=False) assert bound.arguments["arg"] == 1 @pytest.mark.parametrize( argnames=("func", "params"), argvalues=[ (one, ((1, 1), {})), (one, ((), {})), (one, ((1,), {"arg": 1})), (kwd, ((1,), {})), (kwd, ((), {"foo": 1})), (kwarg, ((1, 1), {})), ], ) def test_bind_errors(func, params): args, kwargs = params with pytest.raises(TypeError): typic.bind(func, *args, **kwargs)

[ "sean_stewart@me.com" ]

sean_stewart@me.com

f12efd5ed35fd74e1473fbc7a4e486b309acacb7

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/xcp2k/classes/_hydronium4.py

443fc603162a0a0656a7d260f804120f0b86d348

[]

no_license

superstar54/xcp2k

82071e29613ccf58fc14e684154bb9392d00458b

e8afae2ccb4b777ddd3731fe99f451b56d416a83

refs/heads/master

2021-11-11T21:17:30.292500

2021-11-06T06:31:20

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from xcp2k.inputsection import InputSection from _point66 import _point66 class _hydronium4(InputSection): def __init__(self): InputSection.__init__(self) self.Oxygens = [] self.Hydrogens = [] self.Roo = None self.Pno = None self.Qno = None self.Roh = None self.Pnh = None self.Qnh = None self.Nh = None self.P = None self.Q = None self.Lambda = None self.Lambda = None self.POINT_list = [] self._name = "HYDRONIUM" self._keywords = {'Roh': 'ROH', 'Nh': 'NH', 'P': 'P', 'Roo': 'ROO', 'Q': 'Q', 'Pnh': 'PNH', 'Pno': 'PNO', 'Qno': 'QNO', 'Qnh': 'QNH', 'Lambda': 'LAMBDA'} self._repeated_keywords = {'Oxygens': 'OXYGENS', 'Hydrogens': 'HYDROGENS'} self._repeated_subsections = {'POINT': '_point66'} self._aliases = {'Expon_numerator': 'P', 'Nhtest': 'Nh', 'R_oh': 'Roh', 'Expon_denominator': 'Q', 'R_oo': 'Roo', 'Expon_numeratorb': 'Pnh', 'Expon_numeratora': 'Pno', 'Expon_denominatorb': 'Qnh', 'Expon_denominatora': 'Qno'} self._attributes = ['POINT_list'] def POINT_add(self, section_parameters=None): new_section = _point66() if section_parameters is not None: if hasattr(new_section, 'Section_parameters'): new_section.Section_parameters = section_parameters self.POINT_list.append(new_section) return new_section @property def R_oo(self): """ See documentation for Roo """ return self.Roo @property def Expon_numeratora(self): """ See documentation for Pno """ return self.Pno @property def Expon_denominatora(self): """ See documentation for Qno """ return self.Qno @property def R_oh(self): """ See documentation for Roh """ return self.Roh @property def Expon_numeratorb(self): """ See documentation for Pnh """ return self.Pnh @property def Expon_denominatorb(self): """ See documentation for Qnh """ return self.Qnh @property def Nhtest(self): """ See documentation for Nh """ return self.Nh @property def Expon_numerator(self): """ See documentation for P """ return self.P @property def Expon_denominator(self): """ See documentation for Q """ return self.Q @R_oo.setter def R_oo(self, value): self.Roo = value @Expon_numeratora.setter def Expon_numeratora(self, value): self.Pno = value @Expon_denominatora.setter def Expon_denominatora(self, value): self.Qno = value @R_oh.setter def R_oh(self, value): self.Roh = value @Expon_numeratorb.setter def Expon_numeratorb(self, value): self.Pnh = value @Expon_denominatorb.setter def Expon_denominatorb(self, value): self.Qnh = value @Nhtest.setter def Nhtest(self, value): self.Nh = value @Expon_numerator.setter def Expon_numerator(self, value): self.P = value @Expon_denominator.setter def Expon_denominator(self, value): self.Q = value

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

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/sdk/test/test_filtered_client_payload_list_institution.py

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[ "MIT" ]

permissive

yapily/yapily-sdk-python

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refs/heads/master

2022-12-10T09:24:54.029376

2022-11-25T12:42:30

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2022-02-11T16:57:11

2018-05-18T14:02:57

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""" Yapily API The Yapily API enables connections between your application and users' banks. For more information check out our [documentation](https://docs.yapily.com/).<br><br>In particular, make sure to view our [Getting Started](https://docs.yapily.com/pages/home/getting-started/) steps if this is your first time here.<br><br>While testing the API, our list of [sandbox credentials](https://docs.yapily.com/pages/key-concepts/sandbox-credentials/) maybe useful. # noqa: E501 The version of the OpenAPI document: 2.15.0 Contact: support@yapily.com Generated by: https://openapi-generator.tech """ import sys import unittest import yapily from yapily.model.filter_and_sort import FilterAndSort from yapily.model.institution import Institution globals()['FilterAndSort'] = FilterAndSort globals()['Institution'] = Institution from yapily.model.filtered_client_payload_list_institution import FilteredClientPayloadListInstitution class TestFilteredClientPayloadListInstitution(unittest.TestCase): """FilteredClientPayloadListInstitution unit test stubs""" def setUp(self): pass def tearDown(self): pass def testFilteredClientPayloadListInstitution(self): """Test FilteredClientPayloadListInstitution""" # FIXME: construct object with mandatory attributes with example values # model = FilteredClientPayloadListInstitution() # noqa: E501 pass if __name__ == '__main__': unittest.main()

[ "bitbucket@yapily.com" ]

bitbucket@yapily.com

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/2048.py

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[]

no_license

zhangdavids/2048youxi

9b8fe8dbc851b1a380197bd435b24e079dee7707

aee515288b922f7d353fbf3433b8fecd56d23125

refs/heads/master

2021-01-10T01:44:39.718816

2016-04-03T14:33:18

55,350,492

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#!usr/bin/python #-*- coding:utf-8 -*- #导入需要的包 import curses from random import randrange, choice # generate and place new tile from collections import defaultdict #区分下大小写 letter_codes = [ord(ch) for ch in 'WASDRQwasdrq'] #用户行为 actions = ['Up', 'Left', 'Down', 'Right', 'Restart', 'Exit'] #行为关联 actions_dict = dict(zip(letter_codes, actions * 2)) # 用户处理 def get_user_action(keyboard): char = "N" while char not in actions_dict: char = keyboard.getch() return actions_dict[char] # 矩阵转置 def transpose(field): return [list(row) for row in zip(*field)] # 矩阵逆转 def invert(field): return [row[::-1] for row in field] # 创建棋盘 class GameField(object): def __init__(self, height=4, width=4, win=2048): self.height = height self.width = width self.win_value = 2048 self.score = 0 self.highscore = 0 self.reset() #重置棋盘 def reset(self): if self.score > self.highscore: self.highscore = self.score self.score = 0 self.field = [[0 for i in range(self.width)] for j in range(self.height)] self.spawn() self.spawn() def move(self, direction): def move_row_left(row): def tighten(row): # squeese non-zero elements together new_row = [i for i in row if i != 0] new_row += [0 for i in range(len(row) - len(new_row))] return new_row def merge(row): pair = False new_row = [] for i in range(len(row)): if pair: new_row.append(2 * row[i]) self.score += 2 * row[i] pair = False else: if i + 1 < len(row) and row[i] == row[i + 1]: pair = True new_row.append(0) else: new_row.append(row[i]) assert len(new_row) == len(row) return new_row return tighten(merge(tighten(row))) moves = {} moves['Left'] = lambda field:[move_row_left(row) for row in field] moves['Right'] = lambda field:invert(moves['Left'](invert(field))) moves['Up'] = lambda field:transpose(moves['Left'](transpose(field))) moves['Down'] = lambda field:transpose(moves['Right'](transpose(field))) if direction in moves: if self.move_is_possible(direction): self.field = moves[direction](self.field) self.spawn() return True else: return False def is_win(self): return any(any(i >= self.win_value for i in row) for row in self.field) def is_gameover(self): return not any(self.move_is_possible(move) for move in actions) def draw(self, screen): help_string1 = '(W)Up (S)Down (A)Left (D)Right' help_string2 = ' (R)Restart (Q)Exit' gameover_string = ' GAME OVER' win_string = ' YOU WIN!' def cast(string): screen.addstr(string + '\n') def draw_hor_separator(): line = '+' + ('+------' * self.width + '+')[1:] separator = defaultdict(lambda: line) if not hasattr(draw_hor_separator, "counter"): draw_hor_separator.counter = 0 cast(separator[draw_hor_separator.counter]) draw_hor_separator.counter += 1 def draw_row(row): cast(''.join('|{: ^5} '.format(num) if num > 0 else '| ' for num in row) + '|') screen.clear() cast('SCORE: ' + str(self.score)) if 0 != self.highscore: cast('HGHSCORE: ' + str(self.highscore)) for row in self.field: draw_hor_separator() draw_row(row) draw_hor_separator() if self.is_win(): cast(win_string) else: if self.is_gameover(): cast(gameover_string) else: cast(help_string1) cast(help_string2) def spawn(self): new_element = 4 if randrange(100) > 89 else 2 (i,j) = choice([(i,j) for i in range(self.width) for j in range(self.height) if self.field[i][j] == 0]) self.field[i][j] = new_element def move_is_possible(self, direction): def row_is_left_movable(row): def change(i): # true if there'll be change in i-th tile if row[i] == 0 and row[i + 1] != 0: # Move return True if row[i] != 0 and row[i + 1] == row[i]: # Merge return True return False return any(change(i) for i in range(len(row) - 1)) check = {} check['Left'] = lambda field: \ any(row_is_left_movable(row) for row in field) check['Right'] = lambda field: \ check['Left'](invert(field)) check['Up'] = lambda field: \ check['Left'](transpose(field)) check['Down'] = lambda field: \ check['Right'](transpose(field)) if direction in check: return check[direction](self.field) else: return False def main(stdscr): def init(): #重置游戏棋盘 game_field.reset() return 'Game' def not_game(state): #画出 GameOver 或者 Win 的界面 game_field.draw(stdscr) #读取用户输入得到action，判断是重启游戏还是结束游戏 action = get_user_action(stdscr) responses = defaultdict(lambda: state) #默认是当前状态，没有行为就会一直在当前界面循环 responses['Restart'], responses['Exit'] = 'Init', 'Exit' #对应不同的行为转换到不同的状态 return responses[action] def game(): #画出当前棋盘状态 game_field.draw(stdscr) #读取用户输入得到action action = get_user_action(stdscr) if action == 'Restart': return 'Init' if action == 'Exit': return 'Exit' if game_field.move(action): # move successful if game_field.is_win(): return 'Win' if game_field.is_gameover(): return 'Gameover' return 'Game' state_actions = { 'Init': init, 'Win': lambda: not_game('Win'), 'Gameover': lambda: not_game('Gameover'), 'Game': game } curses.use_default_colors() game_field = GameField(win=32) state = 'Init' #状态机开始循环 while state != 'Exit': state = state_actions[state]() curses.wrapper(main)

[ "1269969739@qq.com" ]

1269969739@qq.com

70d96d19ee9e1ef10f8830c60a370e52578457b6

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/Python/Excel/xlrdwtDemo.py

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[]

no_license

kinscloud/kinscloud.github.io

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refs/heads/master

2022-12-14T22:01:34.245628

2020-05-31T02:49:05

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null

2022-12-08T04:02:36

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UTF-8

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py

import xlrd,xlwt workbook = xlrd.open_workbook("testxls.xls") sheet = workbook.sheet_by_name("Sheet1") title_row = sheet.row(0) # print(title_row[0].value) # print(sheet.nrows) datas = [] for i in range(1,sheet.nrows): data_row = sheet.row(i) data ={} for j in range(sheet.ncols): cell = data_row[j] if cell.ctype == xlrd.XL_CELL_DATE: value = xlrd.xldate_as_datetime(cell.value,0).strftime(("%Y-%m-%d")) elif cell.ctype == xlrd.XL_CELL_NUMBER: value = int(cell.value) else: value = cell.value # print(value) data[title_row[j].value] = value datas.append(data) print(datas) workbook = xlwt.Workbook() sheet = workbook.add_sheet("kins") for i in range(len(title_row)): sheet.write(0,i,title_row[i].value) for i in range(len(datas)): data = datas[i] value_datas = list(data.values()) for j in range((len(value_datas))): sheet.write(i+1,j,value_datas[j]) workbook.save("test2.xlsx")

[ "yuan_haoting@163.com" ]

yuan_haoting@163.com

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/ace/label.py

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chenruixiaoluoye/ACE

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refs/heads/master

2021-01-18T17:51:23.704640

2013-11-07T18:43:13

null

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# from nltk import * import re from collections import Counter class Labeler: ''' Labels articles with features. ''' def __init__(self): pass def extract_word_features(self, text, pattern=r'[^\sa-z\-]+', normalize=None): ''' Takes text from an article as input and returns a dict of features --> weights. ''' patt = re.compile(pattern) clean = patt.sub('', text.lower()) tokens = re.split('\s+', clean) n_words = len(tokens)

[ "tyarkoni@gmail.com" ]

tyarkoni@gmail.com

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/test/test_secureTeaHeaders.py

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rejahrehim/SecureTea-Project

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refs/heads/master

2020-03-27T12:36:21.779426

2019-09-02T16:01:55

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# -*- coding: utf-8 -*- import unittest from securetea.lib.security_header import secureTeaHeaders try: # if python 3.x.x from unittest.mock import patch except ImportError: # python 2.x.x from mock import patch class TestSecureTeaHeaders(unittest.TestCase): """Test class for SecureTeaHeaders.""" def setUp(self): """ Setup test class for SecureTeaHeaders. """ self.securetea_header_obj = secureTeaHeaders.SecureTeaHeaders(url='https://random.com') def test_verify_url(self): """ Test verify_url. """ u1 = "h://random.com" u2 = "http://" u3 = "http://www.random.com" u4 = "https://www.random.com" self.assertFalse(self.securetea_header_obj.verify_url(u1)) self.assertFalse(self.securetea_header_obj.verify_url(u2)) self.assertTrue(self.securetea_header_obj.verify_url(u3)) self.assertTrue(self.securetea_header_obj.verify_url(u4)) @patch('securetea.lib.security_header.secureTeaHeaders.requests') def test_call_url(self, mock_requests): """ Test call_url. """ mock_requests.get.return_value = "random" self.assertEqual("random", self.securetea_header_obj.call_url()) @patch('securetea.lib.security_header.secureTeaHeaders.SecureTeaHeaders.call_url') def test_gather_headers(self, mock_call): """ Test gather_headers. """ mock_call.return_value.headers = "random" headers_dict = self.securetea_header_obj.gather_headers() self.assertEqual("random", headers_dict)

[ "abhishek_official@hotmail.com" ]

abhishek_official@hotmail.com

a01c9e08511b51bf50b3030a1e188422c644b72d

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/migrations/versions/4d0367090b41_.py

3fdcd4b266f4e0ea0f7eee4bb1165c5a559795ed

[]

no_license

chaelysh6z/hanium

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refs/heads/master

2023-08-15T03:59:01.794004

2021-09-25T12:43:19

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"""empty message Revision ID: 4d0367090b41 Revises: 220cbe1a485d Create Date: 2021-09-23 18:30:46.632858 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = '4d0367090b41' down_revision = '220cbe1a485d' branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.add_column('user', sa.Column('gender', sa.Boolean(), nullable=True)) op.add_column('user', sa.Column('age', sa.Integer(), nullable=True)) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.drop_column('user', 'age') op.drop_column('user', 'gender') # ### end Alembic commands ###

[ "renee8369@likelion.org" ]

renee8369@likelion.org

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/tools/c7n_azure/tests_azure/tests_resources/test_recovery_services.py

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permissive

cloud-custodian/cloud-custodian

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refs/heads/main

2023-09-04T10:54:55.963703

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Apache-2.0

2023-09-14T14:03:30

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py

# Copyright The Cloud Custodian Authors. # SPDX-License-Identifier: Apache-2.0 from ..azure_common import BaseTest, arm_template class RecoveryServicesTest(BaseTest): def test_recovery_services_schema_validate(self): with self.sign_out_patch(): p = self.load_policy({ 'name': 'test-recovery-services', 'resource': 'azure.recovery-services' }, validate=True) self.assertTrue(p) @arm_template('recoveryservices.json') def test_find_by_name(self): p = self.load_policy({ 'name': 'test-recovery-services', 'resource': 'azure.recovery-services', 'filters': [ {'type': 'value', 'key': 'name', 'op': 'eq', 'value_type': 'normalize', 'value': 'cfbukqrkhntars655e53akvrc4k'}], }) resources = p.run() self.assertEqual(len(resources), 1)

[ "noreply@github.com" ]

cloud-custodian.noreply@github.com

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/trinity/protocol/eth/events.py

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rampenke/trinity

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refs/heads/master

2020-06-12T13:48:10.579223

2019-06-27T15:20:31

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from dataclasses import ( dataclass, ) from typing import ( List, Tuple, Type, ) from eth.rlp.blocks import BaseBlock from eth.rlp.headers import BlockHeader from eth.rlp.receipts import Receipt from eth.rlp.transactions import BaseTransactionFields from lahja import ( BaseEvent, ) from p2p.kademlia import ( Node, ) from eth_typing import ( BlockIdentifier, Hash32, ) from trinity.protocol.common.events import ( HasRemoteEvent, HasRemoteAndTimeoutRequest, PeerPoolMessageEvent, ) from trinity.protocol.common.types import ( BlockBodyBundles, NodeDataBundles, ReceiptsBundles, ) # Events flowing from PeerPool to Proxy class GetBlockHeadersEvent(PeerPoolMessageEvent): """ Event to carry a ``GetBlockHeaders`` command from the peer pool to any process that subscribes the event through the event bus. """ pass class GetBlockBodiesEvent(PeerPoolMessageEvent): """ Event to carry a ``GetBlockBodies`` command from the peer pool to any process that subscribes the event through the event bus. """ pass class GetReceiptsEvent(PeerPoolMessageEvent): """ Event to carry a ``GetReceipts`` command from the peer pool to any process that subscribes the event through the event bus. """ pass class GetNodeDataEvent(PeerPoolMessageEvent): """ Event to carry a ``GetNodeData`` command from the peer pool to any process that subscribes the event through the event bus. """ pass class TransactionsEvent(PeerPoolMessageEvent): """ Event to carry a ``Transactions`` command from the peer pool to any process that subscribes the event through the event bus. """ pass class NewBlockHashesEvent(PeerPoolMessageEvent): """ Event to carry a ``Transactions`` command from the peer pool to any process that subscribes the event through the event bus. """ pass # Events flowing from Proxy to PeerPool @dataclass class SendBlockHeadersEvent(HasRemoteEvent): """ Event to proxy a ``ETHPeer.sub_proto.send_block_headers`` call from a proxy peer to the actual peer that sits in the peer pool. """ headers: Tuple[BlockHeader, ...] @dataclass class SendBlockBodiesEvent(HasRemoteEvent): """ Event to proxy a ``ETHPeer.sub_proto.send_block_bodies`` call from a proxy peer to the actual peer that sits in the peer pool. """ blocks: List[BaseBlock] @dataclass class SendNodeDataEvent(HasRemoteEvent): """ Event to proxy a ``ETHPeer.sub_proto.send_node_data`` call from a proxy peer to the actual peer that sits in the peer pool. """ nodes: Tuple[bytes, ...] @dataclass class SendReceiptsEvent(HasRemoteEvent): """ Event to proxy a ``ETHPeer.sub_proto.send_receipts`` call from a proxy peer to the actual peer that sits in the peer pool. """ receipts: List[List[Receipt]] @dataclass class SendTransactionsEvent(HasRemoteEvent): """ Event to proxy a ``ETHPeer.sub_proto.send_transactions`` call from a proxy peer to the actual peer that sits in the peer pool. """ transactions: List[BaseTransactionFields] # EXCHANGE HANDLER REQUEST / RESPONSE PAIRS @dataclass class GetBlockHeadersResponse(BaseEvent): headers: Tuple[BlockHeader, ...] exception: Exception = None # noqa: E701 @dataclass class GetBlockHeadersRequest(HasRemoteAndTimeoutRequest[GetBlockHeadersResponse]): remote: Node block_number_or_hash: BlockIdentifier max_headers: int skip: int reverse: bool timeout: float @staticmethod def expected_response_type() -> Type[GetBlockHeadersResponse]: return GetBlockHeadersResponse @dataclass class GetBlockBodiesResponse(BaseEvent): bundles: BlockBodyBundles exception: Exception = None # noqa: E701 @dataclass class GetBlockBodiesRequest(HasRemoteAndTimeoutRequest[GetBlockBodiesResponse]): remote: Node headers: Tuple[BlockHeader, ...] timeout: float @staticmethod def expected_response_type() -> Type[GetBlockBodiesResponse]: return GetBlockBodiesResponse @dataclass class GetNodeDataResponse(BaseEvent): bundles: NodeDataBundles exception: Exception = None # noqa: E701 @dataclass class GetNodeDataRequest(HasRemoteAndTimeoutRequest[GetNodeDataResponse]): remote: Node node_hashes: Tuple[Hash32, ...] timeout: float @staticmethod def expected_response_type() -> Type[GetNodeDataResponse]: return GetNodeDataResponse @dataclass class GetReceiptsResponse(BaseEvent): bundles: ReceiptsBundles exception: Exception = None # noqa: E701 @dataclass class GetReceiptsRequest(HasRemoteAndTimeoutRequest[GetReceiptsResponse]): remote: Node headers: Tuple[BlockHeader, ...] timeout: float @staticmethod def expected_response_type() -> Type[GetReceiptsResponse]: return GetReceiptsResponse

[ "christoph.burgdorf@gmail.com" ]

christoph.burgdorf@gmail.com

a15d6f32d6627ee0cf9e94d8afbfa77f742f459d

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/src/core/w3af/w3af/plugins/attack/db/sqlmap/tamper/bluecoat.py

ff6756e0d26798db31aecb6f8529e3c75d34f196

[]

no_license

ycc1746582381/webfuzzer

8d42fceb55c8682d6c18416b8e7b23f5e430c45f

0d9aa35c3218dc58f81c429cae0196e4c8b7d51b

refs/heads/master

2021-06-14T18:46:59.470232

2017-03-14T08:49:27

null

0

null

UTF-8

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false

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py

#!/usr/bin/env python """ Copyright (c) 2006-2015 sqlmap developers (http://sqlmap.org/) See the file 'doc/COPYING' for copying permission """ import re from lib.core.data import kb from lib.core.enums import PRIORITY __priority__ = PRIORITY.NORMAL def dependencies(): pass def tamper(payload, **kwargs): """ Replaces space character after SQL statement with a valid random blank character. Afterwards replace character = with LIKE operator Requirement: * Blue Coat SGOS with WAF activated as documented in https://kb.bluecoat.com/index?page=content&id=FAQ2147 Tested against: * MySQL 5.1, SGOS Notes: * Useful to bypass Blue Coat's recommended WAF rule configuration >>> tamper('SELECT id FROM users WHERE id = 1') 'SELECT%09id FROM%09users WHERE%09id LIKE 1' """ def process(match): word = match.group('word') if word.upper() in kb.keywords: return match.group().replace(word, "%s%%09" % word) else: return match.group() retVal = payload if payload: retVal = re.sub(r"\b(?P<word>[A-Z_]+)(?=[^\w(]|\Z)", lambda match: process(match), retVal) retVal = re.sub(r"\s*=\s*", " LIKE ", retVal) retVal = retVal.replace("%09 ", "%09") return retVal

[ "everping@outlook.com" ]

everping@outlook.com

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/tests/test_serializer.py

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[ "MIT" ]

permissive

auro-star/html-json-forms

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refs/heads/main

2023-02-21T12:57:34.213464

2020-01-10T02:16:45

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UTF-8

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py

from rest_framework.test import APITestCase from tests.test_app.models import Parent class RestTestCase(APITestCase): def test_submit(self): response = self.client.post('/parents/', { 'name': 'Test', 'children[0][name]': 'Test 1', 'children[1][name]': 'Test 2', }) p = Parent.objects.first() self.assertEqual( { 'id': p.pk, 'name': 'Test', 'children': [ { 'id': p.children.first().pk, 'name': 'Test 1', }, { 'id': p.children.last().pk, 'name': 'Test 2', }, ] }, response.data )

[ "andrew@wq.io" ]

andrew@wq.io

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/docs/examples/__init__.py

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permissive

peterlhn/dash-bootstrap-components

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refs/heads/master

2023-06-11T23:31:30.639330

2021-06-30T09:29:49

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0

Apache-2.0

2020-09-09T08:59:06

2020-09-09T08:59:05

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UTF-8

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py

import os import re from pathlib import Path import dash import dash_bootstrap_components as dbc from jinja2 import Environment, FileSystemLoader from .vendor.graphs_in_tabs import app as git_app from .vendor.iris import app as iris_app HREF_PATTERN = re.compile(r'href="') HERE = Path(__file__).parent EXAMPLES = HERE / "vendor" TEMPLATES = HERE.parent / "templates" GITHUB_EXAMPLES = ( "https://github.com/" "facultyai/dash-bootstrap-components/blob/master/examples/" ) INDEX_STRING_TEMPLATE = """{% extends "example.html" %} {% block head %} {{ super() }} {{ "{%metas%}{%css%}" }} {% endblock %} {% block title %} <title>{{ "{%title%}" }}</title> {% endblock %} <WARNING> {% block content %} {{ "{%app_entry%}" }} {% endblock %} {% block code %}<CODE>{% endblock %} {% block scripts %} <footer> {{ "{%config%}{%scripts%}{%renderer%}" }} {{ super() }} </footer> {% endblock %} """ SIZE_WARNING = """{% block size_warning %} <div class="d-sm-none"> <div class="alert alert-warning"> Warning: This example app has not been optimized for small screens, results may vary... </div> </div> {% endblock %} """ def mod_callback(fn): def wrapper(path, **kwargs): path = path.replace("/examples/simple-sidebar", "") return fn(path, **kwargs) return wrapper def build_app_from_example(app, name, code, code_link, show_warning=False): if show_warning: template = INDEX_STRING_TEMPLATE.replace("<WARNING>", SIZE_WARNING) else: template = INDEX_STRING_TEMPLATE.replace("<WARNING>", "") env = Environment(loader=FileSystemLoader(TEMPLATES.as_posix())) template = env.from_string(template) template = template.render(example_link=code_link) new_app = dash.Dash( external_stylesheets=["/static/loading.css", dbc.themes.BOOTSTRAP], requests_pathname_prefix=f"/examples/{name}/", serve_locally=False, index_string=template.replace("<CODE>", code), update_title=None, ) new_app.title = f"{name.capitalize().replace('-', ' ')} - dbc examples" new_app.layout = app.layout new_app.callback_map = app.callback_map new_app._callback_list = app._callback_list return new_app def register_apps(): iris_app_ = build_app_from_example( iris_app, "iris", (EXAMPLES / "iris.py").read_text(), os.path.join(GITHUB_EXAMPLES, "gallery/iris-kmeans/app.py"), ) git_app_ = build_app_from_example( git_app, "graphs-in-tabs", (EXAMPLES / "graphs_in_tabs.py").read_text(), os.path.join( GITHUB_EXAMPLES, "advanced-component-usage/graphs_in_tabs.py" ), ) # need to do a bit of hackery to make sure the links of the multi page app # work correctly when the app is exposed at a particular route sidebar_source = (EXAMPLES / "simple_sidebar.py").read_text() env = {} exec( HREF_PATTERN.sub('href="/examples/simple-sidebar', sidebar_source), env ) sidebar_app = env["app"] sidebar_app = build_app_from_example( sidebar_app, "simple-sidebar", sidebar_source, os.path.join(GITHUB_EXAMPLES, "multi-page-apps/simple_sidebar.py"), show_warning=True, ) # shim navigation callbacks keys = [ "..page-1-link.active...page-2-link.active...page-3-link.active..", "page-content.children", ] for key in keys: sidebar_app.callback_map[key]["callback"] = mod_callback( sidebar_app.callback_map[key]["callback"] ) return { "/examples/graphs-in-tabs": git_app_, "/examples/iris": iris_app_, "/examples/simple-sidebar": sidebar_app, }

[ "tomcbegley@gmail.com" ]

tomcbegley@gmail.com

8eb52ea6863ebef6d0668ba54548d9644fd3731c

06685fa3aceb620ea13b593ddc52bba53300b93a

/monit/recipes/default.py

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[]

no_license

66laps/kokki-cookbooks

a900f958d346e35a35a05ed6cbb12bbe2f5bf4a4

6c059f8cda577c765083dfe92688094bc38dfd4b

refs/heads/master

2021-01-01T17:00:28.952170

2010-11-20T13:39:52

null

0

null

UTF-8

Python

false

646

py

from kokki import * Package("monit") File("%s/monitrc" % env['monit']['config_path'], owner = "root", group = "root", mode = 0700, content = Template("monit/monitrc.j2")) if env.system.platform == "ubuntu": File("/etc/default/monit", content = Template("monit/default.j2")) Directory("%s/monit.d" % env['monit']['config_path'], owner = "root", group = "root", mode = 0700) Directory("/var/monit", owner = "root", group = "root", mode = 0700) Service("monit", supports_restart = True, subscribes = [('restart', env.resources['File']["%s/monitrc" % env['monit']['config_path']])])

[ "samuel@descolada.com" ]

samuel@descolada.com

131730ae0dfc16ee2405747ef616b9f126049880

d2c4934325f5ddd567963e7bd2bdc0673f92bc40

/tests/artificial/transf_Integration/trend_MovingAverage/cycle_30/ar_/test_artificial_1024_Integration_MovingAverage_30__100.py

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[ "BSD-3-Clause", "LicenseRef-scancode-unknown-license-reference" ]

permissive

jmabry/pyaf

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refs/heads/master

2020-03-20T02:14:12.597970

2018-12-17T22:08:11

137,104,552

0

BSD-3-Clause

2018-12-17T22:08:12

2018-06-12T17:15:43

Python

UTF-8

Python

false

278

py

import pyaf.Bench.TS_datasets as tsds import pyaf.tests.artificial.process_artificial_dataset as art art.process_dataset(N = 1024 , FREQ = 'D', seed = 0, trendtype = "MovingAverage", cycle_length = 30, transform = "Integration", sigma = 0.0, exog_count = 100, ar_order = 0);

[ "antoine.carme@laposte.net" ]

antoine.carme@laposte.net

c6d124b769bc84c50f8a497e6c8e0f524c399100

6600834a4d2455e41a0b587c57f9fc606a39d1cb

/python/dnest4/sampler.py

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[ "MIT" ]

permissive

eggplantbren/DNest4

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refs/heads/master

2023-03-29T21:10:01.725767

2023-03-20T00:09:24

47,721,004

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23

MIT

2021-08-30T11:57:39

2015-12-09T21:46:21

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UTF-8

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false

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py

# -*- coding: utf-8 -*- from .analysis import postprocess from .backends import MemoryBackend try: from ._dnest4 import sample as _sample except ImportError: _sample = None __all__ = ["DNest4Sampler"] class DNest4Sampler(object): def __init__(self, model, backend=None): if _sample is None: raise ImportError("You must build the Cython extensions to use " "the Python API") self._model = model if backend is None: backend = MemoryBackend() self.backend = backend def sample(self, max_num_levels, **kwargs): self.backend.reset() for sample in _sample(self._model, max_num_levels, **kwargs): self.backend.write_particles( sample["samples"], sample["sample_info"] ) self.backend.write_levels(sample["levels"]) yield sample def run(self, num_steps, max_num_levels, **kwargs): if num_steps <= 0: raise ValueError("Invalid number of steps") kwargs["num_steps"] = int(num_steps) for _ in self.sample(max_num_levels, **kwargs): pass def postprocess(self, **kwargs): return postprocess(self.backend, **kwargs)

[ "danfm@nyu.edu" ]

danfm@nyu.edu

60931f9c05009d545e4a09d9160315d49798defd

fa16525085e017babe82a779428aac062e8a72b6

/test/functional/feature_config_args.py

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[ "MIT" ]

permissive

minblock/baetcoin

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8527c30b7c414b479ce7f60c1af31be0afbd63f1

refs/heads/master

2021-05-22T17:12:27.444781

2020-04-04T14:17:21

253,015,556

0

null

UTF-8

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false

5,311

py

#!/usr/bin/env python3 # Copyright (c) 2017-2018 The Bitcoin Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. """Test various command line arguments and configuration file parameters.""" import os from test_framework.test_framework import BitcoinTestFramework class ConfArgsTest(BitcoinTestFramework): def set_test_params(self): self.setup_clean_chain = True self.num_nodes = 1 def test_config_file_parser(self): # Assume node is stopped inc_conf_file_path = os.path.join(self.nodes[0].datadir, 'include.conf') with open(os.path.join(self.nodes[0].datadir, 'baetcoin.conf'), 'a', encoding='utf-8') as conf: conf.write('includeconf={}\n'.format(inc_conf_file_path)) with open(inc_conf_file_path, 'w', encoding='utf-8') as conf: conf.write('-dash=1\n') self.nodes[0].assert_start_raises_init_error(expected_msg='Error reading configuration file: parse error on line 1: -dash=1, options in configuration file must be specified without leading -') with open(inc_conf_file_path, 'w', encoding='utf-8') as conf: conf.write('nono\n') self.nodes[0].assert_start_raises_init_error(expected_msg='Error reading configuration file: parse error on line 1: nono, if you intended to specify a negated option, use nono=1 instead') with open(inc_conf_file_path, 'w', encoding='utf-8') as conf: conf.write('server=1\nrpcuser=someuser\nrpcpassword=some#pass') self.nodes[0].assert_start_raises_init_error(expected_msg='Error reading configuration file: parse error on line 3, using # in rpcpassword can be ambiguous and should be avoided') with open(inc_conf_file_path, 'w', encoding='utf-8') as conf: conf.write('server=1\nrpcuser=someuser\nmain.rpcpassword=some#pass') self.nodes[0].assert_start_raises_init_error(expected_msg='Error reading configuration file: parse error on line 3, using # in rpcpassword can be ambiguous and should be avoided') with open(inc_conf_file_path, 'w', encoding='utf-8') as conf: conf.write('server=1\nrpcuser=someuser\n[main]\nrpcpassword=some#pass') self.nodes[0].assert_start_raises_init_error(expected_msg='Error reading configuration file: parse error on line 4, using # in rpcpassword can be ambiguous and should be avoided') with open(inc_conf_file_path, 'w', encoding='utf-8') as conf: conf.write('testnot.datadir=1\n[testnet]\n') self.restart_node(0) self.nodes[0].stop_node(expected_stderr='Warning: Section [testnet] is not recognized.' + os.linesep + 'Warning: Section [testnot] is not recognized.') with open(inc_conf_file_path, 'w', encoding='utf-8') as conf: conf.write('') # clear def run_test(self): self.stop_node(0) self.test_config_file_parser() # Remove the -datadir argument so it doesn't override the config file self.nodes[0].args = [arg for arg in self.nodes[0].args if not arg.startswith("-datadir")] default_data_dir = self.nodes[0].datadir new_data_dir = os.path.join(default_data_dir, 'newdatadir') new_data_dir_2 = os.path.join(default_data_dir, 'newdatadir2') # Check that using -datadir argument on non-existent directory fails self.nodes[0].datadir = new_data_dir self.nodes[0].assert_start_raises_init_error(['-datadir=' + new_data_dir], 'Error: Specified data directory "' + new_data_dir + '" does not exist.') # Check that using non-existent datadir in conf file fails conf_file = os.path.join(default_data_dir, "baetcoin.conf") # datadir needs to be set before [regtest] section conf_file_contents = open(conf_file, encoding='utf8').read() with open(conf_file, 'w', encoding='utf8') as f: f.write("datadir=" + new_data_dir + "\n") f.write(conf_file_contents) # Temporarily disabled, because this test would access the user's home dir (~/.bitcoin) #self.nodes[0].assert_start_raises_init_error(['-conf=' + conf_file], 'Error reading configuration file: specified data directory "' + new_data_dir + '" does not exist.') # Create the directory and ensure the config file now works os.mkdir(new_data_dir) # Temporarily disabled, because this test would access the user's home dir (~/.bitcoin) #self.start_node(0, ['-conf='+conf_file, '-wallet=w1']) #self.stop_node(0) #assert os.path.exists(os.path.join(new_data_dir, 'regtest', 'blocks')) #if self.is_wallet_compiled(): #assert os.path.exists(os.path.join(new_data_dir, 'regtest', 'wallets', 'w1')) # Ensure command line argument overrides datadir in conf os.mkdir(new_data_dir_2) self.nodes[0].datadir = new_data_dir_2 self.start_node(0, ['-datadir='+new_data_dir_2, '-conf='+conf_file, '-wallet=w2']) assert os.path.exists(os.path.join(new_data_dir_2, 'regtest', 'blocks')) if self.is_wallet_compiled(): assert os.path.exists(os.path.join(new_data_dir_2, 'regtest', 'wallets', 'w2')) if __name__ == '__main__': ConfArgsTest().main()

[ "POSTMASTER@provgn.com" ]

POSTMASTER@provgn.com

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/.history/length_20200528185715.py

3ea39907837c76154f9a178d2a6eea6680302f1a

[]

no_license

MaryanneNjeri/pythonModules

56f54bf098ae58ea069bf33f11ae94fa8eedcabc

f4e56b1e4dda2349267af634a46f6b9df6686020

refs/heads/master

2022-12-16T02:59:19.896129

2020-09-11T12:05:22

null

0

null

UTF-8

Python

false

399

py

def removeDuplicates(nums): length = len(nums) i = 0 for i in range(length): if nums[i] in nums: nums.remove(nums[i]) else: # for i in range(length): # print('i--------->',i) # for j in range(i+1,length): # print('j----->',j) removeDuplicates([1,1,1,2,2])

[ "mary.jereh@gmail.com" ]

mary.jereh@gmail.com

25494d2bd6e4f43fef81a4f5b6eaf97f9b1bf970

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/veci.py

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xCiaraG/Kattis

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def find_next_highest(num): prev = num[-1] i = len(num) - 2 while i > 0 and num[i] >= prev: prev = num[i] i -= 1 last = num[i] if i + 1 < len(num): tmp = num[i+1:] tmp = sorted(tmp) j = 0 while tmp[j] <= last: j += 1 prev = tmp[j] tmp[j] = last num = num[:i] + prev + "".join(sorted(list(tmp))) return num num = input().strip() if list(num) == sorted(num, reverse=True): print("0") else: tmp = find_next_highest(num) print(tmp)

[ "ciara.godwin3@mail.dcu.ie" ]

ciara.godwin3@mail.dcu.ie

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/xai/brain/wordbase/nouns/_rosters.py

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cash2one/xai

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from xai.brain.wordbase.nouns._roster import _ROSTER #calss header class _ROSTERS(_ROSTER, ): def __init__(self,): _ROSTER.__init__(self) self.name = "ROSTERS" self.specie = 'nouns' self.basic = "roster" self.jsondata = {}

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

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/calculaPCT_grasspy_esc10000.py

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[]

no_license

JohnWRRC/Scripts_DelimitaBacias_TrabalhoFinalizado_Tadeu

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import grass.script as grass import os #mapa de vegetacao vegetacao="vegetacao_natural_cli_rast_30m_tif" mapa="mosaic_topodata_30m_extract_tif_10000_30m_vect" length=1 os.chdir(r'E:\data_2015\___john\Tadeu_finlandia\TXTs_PCT\esc_10000') def stats_area(mapa,id_map): id_map=id_map.replace('\n','') acumla_area=0 grass.run_command('g.region',rast=mapa) x=grass.read_command('r.stats',flags='a',input=mapa) y=x.split('\n') del y[-1];del y[-1] #for aculuma area_m2 for i in y: split=i.split(' ') area_m2=float(split[1]) acumla_area=acumla_area+area_m2 txt=open('basin_'+id_map+'.txt','w') cabecalho='id'',''pct_veg\n' txt.write(cabecalho) for i in y: split=i.split(' ') id=split[0] area_m2=float(split[1]) pct=round(area_m2/acumla_area*100,3) txt.write(id+','+`pct`+'\n') txt.close() #stats_area("mapa_soma_int",5965) def create_bins(mapa_temp): vegetacao="vegetacao_natural_cli_rast_30m_tif" expressao1='veg_temp=if('+mapa_temp+'>0,'+vegetacao+',null())' grass.mapcalc(expressao1, overwrite = True, quiet = True) grass.run_command('r.series',inpu='veg_temp,'+mapa_temp,out='mapa_soma',method='sum',overwrite=True) expressao2='mapa_soma_int=int(mapa_soma)' grass.mapcalc(expressao2, overwrite = True, quiet = True) return 'mapa_soma_int' def stats(mapa): grass.run_command('g.region',vect=mapa) con=3116 while con <= 3155: query="id=%d"%con x=grass.read_command('v.db.select', flags='c', map=mapa, column='id', where=query,verbose=False) grass.run_command('v.extract', input=mapa, output='temp', where=query, type='area', new=1,overwrite=True,verbose=False) grass.run_command('v.to.rast', input='temp', out='temp_rast_masc', use="cat",overwrite=True,verbose=False) grass.run_command('r.mask',input="temp_rast_masc",overwrite=True) mapa_soma=create_bins("temp_rast_masc") stats_area(mapa_soma,x) grass.run_command('g.remove',flags='f',rast=mapa_soma+',mapa_soma_int') grass.run_command('g.remove',flags='f',vect='temp') grass.run_command('r.mask',flags='r') grass.run_command('g.remove',flags='f',rast='temp_rast_masc') con=con+1 stats(mapa)

[ "jw.ribeiro.rc@gmail.com" ]

jw.ribeiro.rc@gmail.com

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/eslearn/utils/regression/multi_test2.py

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sysunwenbo/easylearn

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2022-04-18T00:16:56.263547

2020-04-16T15:45:07

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# -*- coding: utf-8 -*- """ Created on Tue Aug 14 20:25:12 2018 @author: lenovo """ def func(msg): print (multiprocessing.current_process().name + '-' + msg) if __name__ == "__main__": pool = multiprocessing.Pool(processes=4) # 创建4个进程 for i in range(10): msg = "hello %d" %(i) pool.apply_async(func, (msg, )) pool.close() # 关闭进程池，表示不能在往进程池中添加进程 pool.join() # 等待进程池中的所有进程执行完毕，必须在close()之后调用 print ("Sub-process(es) done.")

[ "you@example.com" ]

you@example.com