pytorch如何批次遍历数据集打印数据-创新互联
小编给大家分享一下pytorch如何批次遍历数据集打印数据，相信大部分人都还不怎么了解，因此分享这篇文章给大家参考一下，希望大家阅读完这篇文章后大有收获，下面让我们一起去了解一下吧！
代码
from os import listdir
import os
from time import time
import torch.utils.data as data
import torchvision.transforms as transforms
from torch.utils.data import DataLoader
def printProgressBar(iteration, total, prefix='', suffix='', decimals=1, length=100,
fill='=', empty=' ', tip='>', begin='[', end=']', done="[DONE]", clear=True):
percent = ("{0:." + str(decimals) + "f}").format(100 * (iteration / float(total)))
filledLength = int(length * iteration // total)
bar = fill * filledLength
if iteration != total:
bar = bar + tip
bar = bar + empty * (length - filledLength - len(tip))
display = '\r{prefix}{begin}{bar}{end} {percent}%{suffix}' \
.format(prefix=prefix, begin=begin, bar=bar, end=end, percent=percent, suffix=suffix)
print(display, end=''), # comma after print() required for python 2
if iteration == total: # print with newline on complete
if clear: # display given complete message with spaces to 'erase' previous progress bar
finish = '\r{prefix}{done}'.format(prefix=prefix, done=done)
if hasattr(str, 'decode'): # handle python 2 non-unicode strings for proper length measure
finish = finish.decode('utf-8')
display = display.decode('utf-8')
clear = ' ' * max(len(display) - len(finish), 0)
print(finish + clear)
else:
print('')
class DatasetFromFolder(data.Dataset):
def __init__(self, image_dir):
super(DatasetFromFolder, self).__init__()
self.photo_path = os.path.join(image_dir, "a")
self.sketch_path = os.path.join(image_dir, "b")
self.image_filenames = [x for x in listdir(self.photo_path) if is_image_file(x)]
transform_list = [transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))]
self.transform = transforms.Compose(transform_list)
def __getitem__(self, index):
# Load Image
input = load_img(os.path.join(self.photo_path, self.image_filenames[index]))
input = self.transform(input)
target = load_img(os.path.join(self.sketch_path, self.image_filenames[index]))
target = self.transform(target)
return input, target
def __len__(self):
return len(self.image_filenames)
if __name__ == '__main__':
dataset = DatasetFromFolder("./dataset/facades/train")
dataloader = DataLoader(dataset=dataset, num_workers=8, batch_size=1, shuffle=True)
total = len(dataloader)
for epoch in range(20):
t0 = time()
for i, batch in enumerate(dataloader):
real_a, real_b = batch[0], batch[1]
printProgressBar(i + 1, total + 1,
length=20,
prefix='Epoch %s ' % str(1),
suffix=', d_loss: %d' % 1)
printProgressBar(total, total,
done='Epoch [%s] ' % str(epoch) +
', time: %.2f s' % (time() - t0)
)以上是“pytorch如何批次遍历数据集打印数据”这篇文章的所有内容，感谢各位的阅读！相信大家都有了一定的了解，希望分享的内容对大家有所帮助，如果还想学习更多知识，欢迎关注创新互联成都网站设计公司行业资讯频道！
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