batch_size：有多少张
shuffle=True：顺序不打乱
num_workers: 进程数
drop_last：最后不够64张是否舍去
import torchvision
from torch.utils.data import DataLoader # 1
from torch.utils.tensorboard import SummaryWriter test_data = torchvision.datasets.CIFAR10("./dataset", train=False, transform=torchvision.transforms.ToTensor(), download=False) test_loader = DataLoader(dataset=test_data, batch_size=64, shuffle=True, num_workers=0, drop_last=True) #
img, target = test_data[0]
print(img.shape)
print(target) writer = SummaryWriter("dataloader")
for epoch in range(2):
step = 0
for data in test_loader:
imgs, targets = data
# print(imgs.shape)
# print(targets)
writer.add_images("epoch: {}".format(epoch), imgs, step)
step = step+1 writer.close()
