I am having trouble with the dataloader.
normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])

dataset = datasets.ImageFolder(root='images', transform=transforms.Compose([normalize]))
test_loader = torch.utils.data.DataLoader(dataset, batch_size=4, shuffle=True)
for i, (input, target) in enumerate(test_loader):
    pass

Error:
TypeError: zip argument #1 must support iteration
The “images” directory has single subdirectory with single image.