@Hwanil
You can load images using the following code:
traindir = os.path.join(args.data, 'train')
valdir = os.path.join(args.data, 'val')
testdir = os.path.join(args.data, 'test')
normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
train_loader = data.DataLoader(
    datasets.ImageFolder(traindir,
                         transforms.Compose([
                             transforms.RandomSizedCrop(224),
                             transforms.RandomHorizontalFlip(),
                             transforms.ToTensor(),
                             normalize,
                         ])),
    batch_size=args.batch_size,
    shuffle=True,
    num_workers=args.workers,
    pin_memory=True)

val_loader = data.DataLoader(
    datasets.ImageFolder(valdir,
                         transforms.Compose([
                             transforms.Scale(256),
                             transforms.CenterCrop(224),
                             transforms.ToTensor(),
                             normalize,
                         ])),
    batch_size=args.batch_size,
    shuffle=True,
    num_workers=args.workers,
    pin_memory=True)

test_loader = data.DataLoader(
    TestImageFolder(testdir,
                    transforms.Compose([
                        transforms.Scale(256),
                        transforms.CenterCrop(224),
                        transforms.ToTensor(),
                        normalize,
                    ])),
    batch_size=1,
    shuffle=False,
    num_workers=1,

pin_memory=False)