[add] CLEAR10 benchmark (remove assertion for transformation)
@@ -101,12 +101,10 @@ def CLEAR(
e.g. a random crop, a normalization or a concatenation of different
transformations (see torchvision.transform documentation for a
comprehensive list of possible transformations). Defaults to None.
- If returning feature tensors, then train_transform must be None.
:param eval_transform: The transformation to apply to the test data,
e.g. a random crop, a normalization or a concatenation of different
transformations (see torchvision.transform documentation for a
comprehensive list of possible transformations). Defaults to None.
- If returning feature tensors, then eval_transform must be None.
:param dataset_root: The root path of the dataset.
Defaults to None, which means that the default location for
'clear10' will be used.
@@ -138,8 +136,6 @@ def CLEAR(
raise NotImplementedError()
if feature_type is None:
- assert isinstance(train_transform, type(None)), "No image transform"
- assert isinstance(eval_transform, type(None)), "No image transform"
clear_dataset_train = CLEARImage(
root=dataset_root,
data_name=data_name,
@@ -160,8 +156,6 @@ def CLEAR(
test_samples = clear_dataset_test.paths_and_targets
benchmark_generator = create_generic_benchmark_from_paths
else:
- assert isinstance(train_transform, type(None)), "Feature transform"
- assert isinstance(eval_transform, type(None)), "Feature transform"
clear_dataset_train = CLEARFeature(
root=dataset_root,
data_name=data_name,
