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()