test = Omniglot(root=dataset_root, train=False, download=True) return train, test __all__ = [ 'SplitOmniglot', 'PermutedOmniglot', 'RotatedOmniglot' ] if __name__ == "__main__": import sys print('Split Omniglot') benchmark_instance = SplitOmniglot( 4, train_transform=None, eval_transform=None) check_vision_benchmark(benchmark_instance) print('Permuted Omniglot') benchmark_instance = PermutedOmniglot( 5, train_transform=None, eval_transform=None) check_vision_benchmark(benchmark_instance) print('Rotated Omniglot') benchmark_instance = RotatedOmniglot( 5, train_transform=None, eval_transform=None) check_vision_benchmark(benchmark_instance) sys.exit(0)
return nc_benchmark(train_dataset=train_set, test_dataset=test_set, n_experiences=n_experiences, task_labels=False, per_exp_classes=per_exp_classes, seed=seed, fixed_class_order=fixed_class_order, shuffle=shuffle, train_transform=train_transform, eval_transform=eval_transform) def _get_cub200_dataset(root): train_set = CUB200(root, train=True) test_set = CUB200(root, train=False) return train_set, test_set __all__ = ['SplitCUB200'] if __name__ == "__main__": import sys benchmark_instance = SplitCUB200(5, train_transform=Compose( [ToTensor(), Resize((128, 128))])) check_vision_benchmark(benchmark_instance, show_without_transforms=False) sys.exit(0)