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""" 创建狗类 数据: 品种、昵称、身长、体重 行为: 吃(体重增长1) 实例化两个对象并调用其函数 画出内存图 """ # 实例成员通过对象访问 # 通常在类中对象是self # 在类外对象是 “变量=类名(...)” class Dog: def __init__(self, species="", pet_name="", height=0.0, weight=0): self.species = species self.pet_name = pet_name self.height = h...
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# MIT License # # Copyright (c) 2021 Soohwan Kim and Sangchun Ha and Soyoung Cho # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights...
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""" image diffs loss multiple of 100 diff power of .5 """ import os import copy import numpy as np import curiosity.utils.base as base import curiosity.models.future_pred_asymmetric_with_bypass as modelsource import curiosity.datasources.images_futurediffs_and_actions as datasource dbname = 'threeworld_future_pred' ...
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def equi(A): # return the number of equal leaders that both occur in the sequences # first find the equileader # then count them in both sequences store = {} candidate = -1 for i in A: if i in store: store[i] +=1 else: store[i] = 1 for i in s...
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from PyObjCTools.TestSupport import * import Security class Testoidscert(TestCase): def test_unsuppported(self): self.assertFalse(hasattr(Security, "INTEL_X509V3_CERT_R08")) self.assertFalse(hasattr(Security, "INTEL_X509V3_CERT_R08_LENGTH")) self.assertFalse(hasattr(Security, "INTEL_X509V...
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from collections import Default import json import sys sys.path.join('..') from SETTINGS import DATA_DIR RESULTS_PATH = os.path.join( DATA_DIR, 'crowdflower', 'results-binary-comprehensive.json') def read_raw_results(results_path=RESULTS_PATH): d = [json.loads(l) for l in open(results_path)] def results_by_contr...
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""" .. See the NOTICE file distributed with this work for additional information regarding copyright ownership. 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....
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from __future__ import print_function, division import matplotlib matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab! from neuralnilm import Net, RealApplianceSource, BLSTMLayer, DimshuffleLayer from lasagne.nonlinearities import sigmoid, rectify from lasagne.objectives import crossentropy, mse...
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import os PROJECT_ROOT = os.path.abspath(os.path.dirname(os.path.dirname(__file__))) ROOT_URLCONF = 'standalone_django_project.urls' WSGI_APPLICATION = 'standalone_django_project.wsgi.application' SITE_ID = 1 SITE_NAME = os.environ.get("SITE_NAME") SITE_DOMAIN = os.environ['SITE_DOMAIN'] HEROKU_DOMAIN = os.environ.ge...
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#-*- coding: utf-8 -*- """ A TestRunner for use with the Python unit testing framework. It generates a HTML report to show the result at a glance. The simplest way to use this is to invoke its main method. E.g. import unittest import HTMLTestRunner ... define your tests ... if __name__ == '__main__'...
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#!/usr/bin/env python import rospy from gps_dnn_policy_training_and_testing_pkg.CONSTANT import training_request_topic, training_response_topic from gps_dnn_policy_training_and_testing_pkg.dnn_policy import DnnPolicy from std_msgs.msg import String import pdb import pickle import tempfile def cb(msg): rospy.login...
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def getDels(x): for i in range(1, x+1): if x % i == 0: yield i for x in range(180131, 180179): dels = list(getDels(x)) if len(dels) == 6: print(dels[-2], dels[-1])
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#!/usr/bin/env python import argparse import numpy as np import torch import torch.nn as nn from rev2.cifar10.model_utils import resnet50, CIFAR10_RESNET50_CKPT_PATH from rev2.gs.generate_gs import generate_gs from rev2.cifar10.data_utils import cifar10_normalize from rev2.cifar10.generate_gs_benign import cifar10_re...
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"""Tracer code for Forage model development.""" import os import natcap.invest.forage import logging logging.basicConfig(level=logging.DEBUG) LOGGER = logging.getLogger('forage_tracer') POSSIBLE_DROPBOX_LOCATIONS = [ r'D:\Dropbox', r'C:\Users\Rich\Dropbox', r'C:\Users\rpsharp\Dropbox', r...
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#!/usr/bin/env python # -*- coding: cp1251 -*- ################################################## ## DEPENDENCIES import sys import os import os.path from os.path import getmtime, exists import time import types import __builtin__ from Cheetah.Version import MinCompatibleVersion as RequiredCheetahVersion from Cheeta...
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# coding=utf8 import tensorflow as tf from tensorflow.models.rnn import rnn_cell from tensorflow.models.rnn import seq2seq import numpy as np class Model(): def __init__(self, args, infer=False): self.args = args if infer: args.batch_size = 1 args.seq_length = 1 if...
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# # The Python Imaging Library. # $Id$ # # optional color managment support, based on Kevin Cazabon's PyCMS # library. # # History: # 2009-03-08 fl Added to PIL. # # Copyright (C) 2002-2003 Kevin Cazabon # Copyright (c) 2009 by Fredrik Lundh # # See the README file for information on usage and redistribution. See # ...
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# A resizable list of integers class Vector(object): items: [int] = None size: int = 0 def __init__(self:"Vector"): self.items = [0] # Returns current capacity def capacity(self:"Vector") -> int: return len(self.items) # Increases capacity of vector by one element def incr...
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""" Copyright (c) 2016-17 Keith Sterling http://www.keithsterling.com Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, mod...
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#!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2017/10/31 下午7:34 # @Author : Hou Rong # @Site : # @File : img_hash.py # @Software: PyCharm import imagehash from PIL import Image from proj.my_lib.logger import get_logger, func_time_logger logger = get_logger("img_hash") @func_time_logger def _img_...
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""" https://leetcode.com/problems/shift-2d-grid/ """ class Solution: def shiftGrid(self, grid: list[list[int]], k: int) -> list[list[int]]: R, C = len(grid), len(grid[0]) newGrid = [[0] * C for _ in range(R)] for r, row in enumerate(grid): for c, v in enumerate(row): ...
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import pdf_to_json as p2j import json url = "file:data/multilingual/Latn.TPI/Mono_8/udhr_Latn.TPI_Mono_8.pdf" lConverter = p2j.pdf_to_json.pdf_to_json_converter() lConverter.mImageHashOnly = True lDict = lConverter.convert(url) print(json.dumps(lDict, indent=4, ensure_ascii=False, sort_keys=True))
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n=int(input()) res=[] for _ in range(n): res.append(int(input())) def findcloset(n): k=0 while n>=pow(2,k): if n<pow(2,k+1): if n==pow(2,k): return pow(2,k) else: return pow(2,k+1) k+=1 for t in res: print(findcloset(t))
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#!/usr/bin/env python # -*- coding: utf-8 -*- # @Date : 2018-04-11 14:45:12 # @Author : guangqiang_xu ([email protected]) # @Link : http://www.treenewbee.com/ # @Version : $Id$ import requests from lxml import etree from retry import retry import time import json import hashlib import re import urllib, urllib2 f...
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import asyncio import logging from datetime import datetime from aiowebsocket.converses import AioWebSocket import json async def startup(uri): async with AioWebSocket(uri) as aws: converse = aws.manipulator # 客户端给服务端发送消息 await converse.send('{"event":"pusher:subscribe","data":{"channel"...
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import pygame pygame.init() # 创建游戏窗口 screen = pygame.display.set_mode((480, 700)) bg = pygame.image.load("./images/background.png") screen.blit(bg, (0, 0)) hero = pygame.image.load("./images/me1.png") screen.blit(hero, (200, 500)) pygame.display.update() pygame.quit()
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# -*- coding: utf-8 -*- # Define here the models for your spider middleware # # See documentation in: # https://doc.scrapy.org/en/latest/topics/spider-middleware.html from scrapy import signals class BaomihuaSpiderMiddleware(object): # Not all methods need to be defined. If a method is not defined, # scrapy...
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################################################## # CampaignCriterionService_services.py # generated by ZSI.generate.wsdl2python ################################################## from CampaignCriterionService_services_types import * import urlparse, types from ZSI.TCcompound import ComplexType, Struct from ZSI im...
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# -*- coding: utf-8 -*- # Generated by Django 1.11.5 on 2017-09-08 08:05 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion import imagekit.models.fields from ...base.utils import Uuid4Upload class Migration(migrations.Migration): dependencies = [ ...
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from django.apps import AppConfig class PersonalservicesConfig(AppConfig): name = 'personalservices'
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106. Construct Binary Tree from Inorder and Postorder Traversal Given inorder and postorder traversal of a tree, construct the binary tree. Note: You may assume that duplicates do not exist in the tree. # Definition for a binary tree node. # class TreeNode(object): # def __init__(self, x): # self.val = x...
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from django.contrib import admin from app.admin import UserFilter from carts.models import Cart @admin.register(Cart) class CartAdmin(admin.ModelAdmin): list_display = [ 'id', 'user', 'total', 'active', ] list_display_links = [ 'id', 'user', 'to...
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# path.py #acl All:read #format PYTHON # -*- coding: iso-8859-1 -*- """ path.py - An object representing a path to a file or directory. Example: from path import path d = path('/home/guido/bin') for f in d.files('*.py'): f.chmod(0755) This module requires Python 2.2 or later. URL: http://www.jorendorff.c...
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from django.shortcuts import render from rest_framework import generics from rest_framework import mixins from django.contrib.auth.models import User from rest_framework import permissions from rest_framework.decorators import api_view from rest_framework.response import Response from rest_framework.reverse import r...
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""" Created on Fri Sep 06 21:03:27 2013 PHYS 613, Assignment 2 Nick Crump """ # Exercise 2.13 # Exercise 2.14 """ From Computational Physics by Devries """ from math import sin,cos,exp,sqrt import numpy as np import matplotlib.pyplot as plt # define function - even state solutions of 1D finite square well potential...
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""" SeleniumBase console scripts runner Usage: seleniumbase [COMMAND] [PARAMETERS] OR sbase [COMMAND] [PARAMETERS] Examples: sbase install chromedriver sbase mkdir ui_tests sbase mkfile new_test.py sbase options sbase convert webdriver_unittest_file.py sbase print my_first_test.py -n sbase translate my_first_test...
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#!/usr/bin/env python import os import sys if __name__ == "__main__": os.environ.setdefault("DJANGO_SETTINGS_MODULE", "anand_crowdbotics_16.settings") try: from django.core.management import execute_from_command_line except ImportError: # The above import may fail for some other reason. Ens...
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#!/usr/bin/env python3 #-*- coding: utf-8 -*- __author__ = 'hstking [email protected]' pcUserAgent = { "safari 5.1 – MAC":"User-Agent:Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_8; en-us) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50", "safari 5.1 – Windows":"User-Agent:Mozilla/5.0 (Windows; U...
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n, m = map(int, input().split()) i = 0 c = 0 while (i + 1) + i < (n - i - (i + 1)) and c < m: print(i + 1, n - i) c += 1 i += 1 a = n // 2 + n % 2 for i in range(m - c): print(a - i - 1, a + i + 1)
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# # Solution to Project Euler problem 146 # by Project Nayuki # # https://www.nayuki.io/page/project-euler-solutions # https://github.com/nayuki/Project-Euler-solutions # import eulerlib # Right off the bat, we can exclude 90% of the candidates by the following observations: # - If n = 1 mod 2, then n^2 + 1 = 0 m...
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import tensorflow as tf import prettytensor as pt import numpy as np class NetWork(object): """ Net work for the encode_decode architechture. """ def __init__(self, batch_size): input_tensor = tf.placeholder(tf.float32, shape=(batch_size, DATA_SIZE)) label_tensor = tf.placeholder(tf.fl...
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# -*- coding: utf-8 -*- import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models from django.contrib.auth import get_user_model User = get_user_model() class Migration(SchemaMigration): def forwards(self, orm): # Adding model 'Notification' db.cr...
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from datetime import datetime as dt, timedelta as td def week_after(d): return (dt.strptime(d, '%d/%m/%Y') + td(days=7)).strftime('%d/%m/%Y')
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# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may ...
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# coding: utf-8 import sys from common.src.main.python.utils.hdfs_generic import * import argparse import os import sys import time from pyspark.sql.functions import (udf, col, decode, when, ...
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# 123.py -- Best time to buy and sell stock III ''' Say you have an array for which the ith element is the price of a given stock on day i. Design an algorithm to find the maximum profit. You may complete at most two transactions. Note: You may not engage in multiple transactions at the same time (i.e., you must sel...
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#!/usr/bin/env python # encoding: utf-8 """ @author: HuRuiFeng @file: Method.py @time: 2019/9/16 16:55 @desc: 方法信息 """ from ch08.classfile.MemberInfo import MemberInfo from ch08.rtda.heap import AccessFlags from ch08.rtda.heap.ClassMember import ClassMember from ch08.rtda.heap.MethodDescriptorParser import MethodDescri...
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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('library', '0010_journal_is_in_fixture'), ] operations = [ migrations.AlterField( model_name='paper', ...
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def sort_by_string(lst, txt): sorts = list(txt) letters = [] for word in lst: letters.append(word[0]) for char in sorts: if char not in letters: sorts.remove(char) newlst = [] for char in sorts: for word in lst: if word[0] == char: newlst.append(word) return newlst
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#!/bin/python #-*- coding=utf-8 -*- import re import json DEBUG = False x = re.compile("(?P<IsValuationAccountCode>\()?(?P<AccountCode>\d\d\d\d)\)?,(?P<rest>.+)") start_end = re.compile("\[(?P<start>\d\d\d\d)-(?P<end>\d\d\d\d)\]") class IDNode(object): def __init__(self, code, title, isvaluation, start, end, n...
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import re from pyramid_debugtoolbar.tbtools import Traceback from pyramid_debugtoolbar.panels import DebugPanel from pyramid_debugtoolbar.utils import escape from pyramid_debugtoolbar.utils import STATIC_PATH from pyramid_debugtoolbar.utils import ROOT_ROUTE_NAME from pyramid_debugtoolbar.utils import EXC_ROUTE_NAME ...
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#!/usr/bin/python3 """Module to define a rectangle Args: width (int): width of a rectangle height (int): height of a rectangle """ class Rectangle: """Rectangle class """ number_of_instances = 0 print_symbol = '#' def __init__(self, width=0, height=0): """Initializes R...
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# # Copyright (C) 2016 The Android Open Source Project # # 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 la...
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# coding=utf-8 # Copyright 2022 The Salesforce Team Authors and The HuggingFace Team. 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/licens...
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#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import logging from classy_vision.generic.profiler import ( ClassyProfilerNotImplementedError, compute_activat...
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from _PyDistributionBase import PyDistributionBase from _ProbDistExt import * class Dirichlet(DirichletDistBase, PyDistributionBase): #---+----|----+----|----+----|----+----|----+----|----+----|----+----| """ Represents the multivariate Dirichlet probability distribution. *** Not finished documenting t...
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import numpy as np from tensorflow.keras.datasets import mnist from tensorflow.keras.models import Sequential,Model from tensorflow.keras.layers import Dense,Dropout,Input,Conv2D (x_train, y_train),(x_test,y_test)= mnist.load_data() from tensorflow.keras.utils import to_categorical y_train = to_categorical(y_train) ...
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N = int(input()) if 90<=N: print("A") elif 80<=N: print("B") elif 70<=N: print("C") elif 60<=N: print("D") else: print("F")
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#!/usr/bin/env python # -*- coding: utf-8 -*- # # Copyright (C) 2012 Glencoe Software, Inc. All Rights Reserved. # Use is subject to license terms supplied in LICENSE.txt # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # th...
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# coding=utf-8 # Copyright 2021 The HuggingFace Inc. team. 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 r...
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# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may ...
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pi,qi=map(int,input().split()) l=list(map(int,input().split())) for i in range(qi): r,s=map(int,input().split()) t1 = l[r-1:s] u1 = t1[0] for i in range(1,len(t1)): u1 = u1 ^ t1[i] print(u1)
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import numpy as np from pymoo.util.misc import at_least_2d_array, to_1d_array_if_possible class Decomposition: def __init__(self, eps=0.0, _type="auto", **kwargs) -> None: super().__init__() self.eps = eps self._type = _type self.ideal_point, self.utopian_point, self.nadir_point ...
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""" Creates assembly of top and bottom plates for hallway arena """ from py2scad import * from assembly import Assembly from hallway_top_plate import Hallway_Top_Plate from hallway_bottom_plate import Hallway_Bottom_Plate class Hallway_Plate_Assembly(Assembly): def make(self): # Create components ...
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x = input() y = input() ans = 'Yes' for i in range(len(x)): if x[i] != y[i]: ans = 'No' print(ans)
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from collections import OrderedDict from distutils.version import LooseVersion from typing import List from typing import Tuple from typing import Union import torch from torch_complex.tensor import ComplexTensor from espnet.nets.pytorch_backend.conformer.encoder import ( Encoder as ConformerEncoder, # noqa: H30...
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''' Glue for returning descriptive statistics. ''' import numpy as np from scipy import stats import os from statsmodels.stats.descriptivestats import sign_test ############################################# # #============================================ # Univariate Descriptive Statistics #=====================...
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#!/usr/bin/env python # Copyright 2014-2019 The PySCF Developers. 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 # # U...
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_base_ = ['../../../../_base_/datasets/jhmdb.py'] log_level = 'INFO' load_from = 'https://download.openmmlab.com/mmpose/top_down/resnet/res50_mpii_256x256-418ffc88_20200812.pth' # noqa: E501 resume_from = None dist_params = dict(backend='nccl') workflow = [('train', 1)] checkpoint_config = dict(interval=1) evaluation ...
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"""Copy Task NTM model.""" from attr import attrs, attrib, Factory import random import numpy as np import torch from torch import nn from torch import optim from model import Model from model import ModelParams class CopyTask(object): def __init__(self): self.model = CopyTaskModel self.param =...
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# Definition for a binary tree node. class TreeNode: def __init__(self, x): self.val = x self.left = None self.right = None class Solution: def maxDepth(self, root: TreeNode) -> int: def helper(node): if node is None: return 0 return 1 + ...
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"""added scopus ID field Revision ID: 5a9e6291a59c Revises: 42f544489b96 Create Date: 2019-03-25 07:05:06.087909 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = '5a9e6291a59c' down_revision = '42f544489b96' branch_labels = None depends_on = None def upgrade()...
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import collections class SnakeGame(object): def __init__(self, width,height,food): """ Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first fo...
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from json_model import JsonModel import importlib def import_class(name): mod_path = '.'.join(name.split('.')[:-1]) cls_name = name.split('.')[-1] mod = importlib.import_module(mod_path) if hasattr(mod, cls_name): attr = getattr(mod, cls_name) if isinstance(attr, type): ret...
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lista=['janeiro', 'fevereiro', 'março', 'abril', 'maio', 'junho', 'julho', 'agosto', 'setembro', 'outubro', 'novembro', 'dezembro'] print (lista[int(input('numero do mes: '))-1])
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import os import tkinter as tk import tkinter.filedialog import json from make_dict import * left_data = None right_data = None debug = False now_select = "" def log(s): logarea.insert("end", f"{s}\n") def make_model_data(): log("模範解答を選択してください") file_path = tk.filedialog.askopenfilename( filety...
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from abc import ABCMeta, abstractmethod import Monstr.Core.DB as DB import Monstr.Core.Utils as Utils import Monstr.Core.Config as Config import Monstr.Core.Constants as Constants # ,----------------------. # |BaseNodule | # |----------------------| # |+string name | # |+obj table_schemas | # |-...
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import os def job_dir(settings): path = settings['JOBDIR'] if path and not os.path.exists(path): os.makedirs(path) return path
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# -*- coding: utf-8 - # # This file is part of offset. See the NOTICE for more information. import fcntl import os import time def nanotime(s=None): """ convert seconds to nanoseconds. If s is None, current time is returned """ if s is not None: return s * 1000000000 return time.time() * 1000...
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# Embedded file name: ./upgradeMisc.py import math import subprocess import re import os import datetime import time import logging import shutil import glob from ast import literal_eval RED = '\x1b[31m' GREEN = '\x1b[32m' YELLOW = '\x1b[33m' RESETCOLORS = '\x1b[0m' def checkDiskspace(backupItemsList):...
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def perfect_number(number): list_of_devisors = [] # for devisor in range(1, number): # if number % devisor == 0: # list_of_devisors.append(devisor) # # if sum(list_of_devisors) == number: # print("We have a perfect number!") # else: # print("It's not so perfect.") list_of_devisors = [devis...
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""" Rsync自动化备份 """ import paramiko import re class RsyncBackup(object): """ Rsync备份: 单一安装Rsync 集体安装Rsync 配置Rsync 多个模块 添加虚拟用户 启动服务 配置密码文件 设置开机自启 服务端/客户端 执行Rsync的命令选项 执行Rsync的参数:服务器端文件地址,虚拟用户名,IP地址,模块名称 """ def __init__...
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d = ("deposito inicial: ") j = ("taxa de juros: ") i = 0 while i < 23: t = d + (1 + j) ** i print ({t:.2f})
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# coding:utf-8 ''' @author: Jason.F @data: 2019.07.12 @function: Implementation: SVDBias Datatset: Pinterest-20 Evaluation: hitradio,ndcg Squared loss function with explicit rating. ''' import pandas as pd import numpy as np import math from collections import defaultdic...
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# -*- coding: utf-8 -*- """ @Author: Lyzhang @Date: @Description: """ import torch import torch.nn as nn import torch.nn.functional as func from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence from config import * from model.SEG_BOT.pointer import Pointer class Segment_Model(nn.Mod...
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# This file is a part of Arjuna # Copyright 2015-2021 Rahul Verma # Website: www.RahulVerma.net # 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...
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class Solution: def twoSum(self, nums: List[int], target: int) -> List[int]: n = len(nums) for i in range(n): for j in range(i+1,n): if nums[i] + nums[j] == target: return [i,j]
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"""Config for the `config-f` setting in StyleGAN2.""" _base_ = [ '../_base_/datasets/ffhq_flip.py', '../_base_/models/stylegan/stylegan2_base.py', '../_base_/default_runtime.py' ] model = dict(generator=dict(out_size=512), discriminator=dict(in_size=512)) data = dict( samples_per_gpu=3, train=dic...