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)
