def build_dataset()

in transfer/datasets.py [0:0]

• 37 lines of code
• 8 McCabe index (conditional complexity)

def build_dataset(is_train, args):
    transform = build_transform(is_train, args)

    if args.data_set == 'imagenet':
        raise NotImplementedError("Only [cifar10, cifar100, flowers, pets] are supported; \
                for imagenet end-to-end finetuning, please refer to the instructions in the main README.")
    
    if args.data_set == 'imagenet':
        root = os.path.join(args.data_path, 'train' if is_train else 'val')
        dataset = datasets.ImageFolder(root, transform=transform)
        nb_classes = 1000

    elif args.data_set == 'cifar10':
        dataset = datasets.CIFAR10(root=args.data_path,
                                    train=is_train,
                                    download=True,
                                    transform=transform)
        nb_classes = 10
    elif args.data_set == "cifar100":
        dataset = datasets.CIFAR100(root=args.data_path,
                                     train=is_train,
                                     download=True,
                                     transform=transform)
        nb_classes = 100
    elif args.data_set == "flowers":
        dataset = oxford_flowers_dataset.Flowers(root=args.data_path, 
                                     train=is_train,
                                     download=False,
                                     transform=transform)
        nb_classes = 102
    elif args.data_set == "pets":
        dataset = oxford_pets_dataset.Pets(root=args.data_path,
                                     train=is_train,
                                     download=False,
                                     transform=transform)
        nb_classes = 37
    else:
        raise NotImplementedError("Only [cifar10, cifar100, flowers, pets] are supported; \
                for imagenet end-to-end finetuning, please refer to the instructions in the main README.")

    return dataset, nb_classes