def build_dataset()

in datasets.py [0:0]

• 29 lines of code
• 10 McCabe index (conditional complexity)

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

    print("Transform = ")
    if isinstance(transform, tuple):
        for trans in transform:
            print(" - - - - - - - - - - ")
            for t in trans.transforms:
                print(t)
    else:
        for t in transform.transforms:
            print(t)
    print("---------------------------")

    if args.data_set == 'CIFAR':
        dataset = datasets.CIFAR100(args.data_path, train=is_train, transform=transform, download=True)
        nb_classes = 100
    elif args.data_set == 'IMNET':
        print("reading from datapath", args.data_path)
        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 == "image_folder":
        root = args.data_path if is_train else args.eval_data_path
        dataset = datasets.ImageFolder(root, transform=transform)
        nb_classes = args.nb_classes
        assert len(dataset.class_to_idx) == nb_classes
    else:
        raise NotImplementedError()
    print("Number of the class = %d" % nb_classes)

    return dataset, nb_classes