imagenet_dataloader

train_dir = '../../../Data/ILSVRC2012/train'
val_dir = '../../../Data/ILSVRC2012/val'
size = 224
batch_size = 32
num_workers = 8 
data_transforms = {
    'train': transforms.Compose([
        transforms.CenterCrop(size),
        transforms.RandomHorizontalFlip(),
        transforms.ToTensor(),
        transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
    ]),
    'val': transforms.Compose([
        transforms.CenterCrop(size),
        transforms.ToTensor(),
        transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
    ])
}
image_datasets = {
    'train': ImageFolder(train_dir,   transform=data_transforms['train']),
    'val': ImageFolder(val_dir, transform=data_transforms['val']),
}
data_loader = {
    x: torch.utils.data.DataLoader(image_datasets[x],
                                   batch_size=batch_size,
                                   shuffle=True,
                                   num_workers=num_workers) for x in ['train', 'val']
}