import numpy as np import tensorflow as tf from tqdm import tqdm def download_and_load_gpt2(model_size, models_dir): # Validate model size allowed_sizes = ("124M", "355M", "774M", "1558M") if model_size not in allowed_sizes: raise ValueError(f"Model size not in {allowed_s...
import re from bs4 import BeautifulSoup from contextlib import closing from tqdm import tqdm import time """ Author: Jack Cui Wechat: https://mp.weixin.qq.com/s/OCWwRVDFNslIuKyiCVUoTA """ # 创建保存目录 save_dir = '妖神记' if save_dir not in os.listdir('./'): os.mkdir(save_dir...
transformsfromtorch.utils.dataimportDataLoaderfromtimm.utilsimportModelEmaV3#pip install timmfromtqdmimporttqdm#pip install tqdmimportmatplotlib.pyplotasplt#pip install matplotlibimporttorch.optimasoptimimportnumpyasnpclassSinusoidal
import torchvision.transforms as transforms import torch.optim as optim import torchvision.transforms.functional as FT from tqdm import tqdm from torch.utils.data import DataLoader from model import Yolov1 from dataset import VOCDataset from utils import ( non_max_suppression, mean_average_precision, ...
tqdm import tqdm import gmpy2 class success(Exception): pass def attack_weak_prime(basenum, exp, n): m = basenum^exp k = len(n.strbase=basenum))//(2*exp) + 1 c = gmpy2.iroot(2*k^3, int(2)) # assert c[1] == True tmp = int(c[0]) try: for c in tqdm(range(1,...
ui import WebDriverWait from selenium.webdriver.support import expected_conditions as EC from selenium.webdriver.common.by import By from selenium.webdriver.chrome.options import Options from tqdm import tqdm_notebook base_url = "https://trustpilot.com" def get_soup(url): return BeautifulSoup(...
tqdm (pronounced taqadum for âprogressâ in Arabic) is a great library for progress bars in Python. It supports conventional loops, e.g., by using tqdm_range instead of range, and it supports Pandas by providing progress_map and progress_apply operations on dataframes.3 ...
原文链接:http://www.cnblogs.com/LuDuo/p/10572013.html 利用Python计算π的值,并显示进度条 第一步:下载tqdm第二步;编写代码frommathimport*fromtqdmimporttqdmfromtimeimport* total,s,n,t=0.0,1,1.0,1.0 clock() while(fabs 成功解决tempfile.py", from random import Random as _Random ImportError: ca...
We will import functional as F from torch.nn, DataLoader from torch.utils.data to create mini-batch sizes, save_image from torchvision.utils to save some fake samples, log2 and sqrt form math, Numpy for linear algebra, os for interaction with the operating system, tqdm to show progress bar...
rsa_components = (n1, e,int(d1), p, q1) myrsa = RSA.construct(rsa_components) private =open('private.pem','w') private.write(myrsa.exportKey()) private.close() rsakey = RSA.importKey(myrsa.exportKey()) rsakey = PKCS1_OAEP.new(rsakey) ...