I know that I can use the following methods to obtain training and validation datasets.
testset = torchvision.datasets.CIFAR10(root=’./data’, train=False,
download=True, transform=transform)
testloader = torch.utils.data.DataLoader(testset, batch_size=1,
shuffle=False, num_workers=2)
but I now want to divide the verification dataset into two variables, images and labels, and save them as .npy files using numpy.save. What are the possible ways? ?
thanks.