@@ -206,9 +206,6 @@ def inject_fake_data(self, tmpdir, config):
206206
207207 return num_images_per_category * len (categories )
208208
209- def test_transforms_v2_wrapper (self ):
210- datasets_utils .check_transforms_v2_wrapper (self )
211-
212209
213210class WIDERFaceTestCase (datasets_utils .ImageDatasetTestCase ):
214211 DATASET_CLASS = datasets .WIDERFace
@@ -486,9 +483,6 @@ def test_class_to_idx(self):
486483 actual = dataset .class_to_idx
487484 assert actual == expected
488485
489- def test_transforms_v2_wrapper (self ):
490- datasets_utils .check_transforms_v2_wrapper (self )
491-
492486
493487class CIFAR100 (CIFAR10TestCase ):
494488 DATASET_CLASS = datasets .CIFAR100
@@ -503,9 +497,6 @@ class CIFAR100(CIFAR10TestCase):
503497 categories_key = "fine_label_names" ,
504498 )
505499
506- def test_transforms_v2_wrapper (self ):
507- datasets_utils .check_transforms_v2_wrapper (self )
508-
509500
510501class CelebATestCase (datasets_utils .ImageDatasetTestCase ):
511502 DATASET_CLASS = datasets .CelebA
@@ -901,9 +892,6 @@ def _create_annotation_file(self, root, name, video_files):
901892 with open (pathlib .Path (root ) / name , "w" ) as fh :
902893 fh .writelines (f"{ str (file ).replace (os .sep , '/' )} \n " for file in sorted (video_files ))
903894
904- def test_transforms_v2_wrapper (self ):
905- datasets_utils .check_transforms_v2_wrapper (self , config = dict (output_format = "TCHW" ))
906-
907895
908896class LSUNTestCase (datasets_utils .ImageDatasetTestCase ):
909897 DATASET_CLASS = datasets .LSUN
@@ -1073,9 +1061,6 @@ def _create_split_files(self, root, video_files, fold, train):
10731061
10741062 return num_train_videos if train else (num_videos - num_train_videos )
10751063
1076- def test_transforms_v2_wrapper (self ):
1077- datasets_utils .check_transforms_v2_wrapper (self , config = dict (output_format = "TCHW" ))
1078-
10791064
10801065class OmniglotTestCase (datasets_utils .ImageDatasetTestCase ):
10811066 DATASET_CLASS = datasets .Omniglot
@@ -1487,9 +1472,6 @@ def _magic(self, dtype, dims):
14871472 def _encode (self , v ):
14881473 return torch .tensor (v , dtype = torch .int32 ).numpy ().tobytes ()[::- 1 ]
14891474
1490- def test_transforms_v2_wrapper (self ):
1491- datasets_utils .check_transforms_v2_wrapper (self )
1492-
14931475
14941476class FashionMNISTTestCase (MNISTTestCase ):
14951477 DATASET_CLASS = datasets .FashionMNIST
@@ -1641,9 +1623,6 @@ def test_classes(self, config):
16411623 assert len (dataset .classes ) == len (info ["classes" ])
16421624 assert all ([a == b for a , b in zip (dataset .classes , info ["classes" ])])
16431625
1644- def test_transforms_v2_wrapper (self ):
1645- datasets_utils .check_transforms_v2_wrapper (self )
1646-
16471626
16481627class ImageFolderTestCase (datasets_utils .ImageDatasetTestCase ):
16491628 DATASET_CLASS = datasets .ImageFolder
@@ -1665,9 +1644,6 @@ def test_classes(self, config):
16651644 assert len (dataset .classes ) == len (info ["classes" ])
16661645 assert all ([a == b for a , b in zip (dataset .classes , info ["classes" ])])
16671646
1668- def test_transforms_v2_wrapper (self ):
1669- datasets_utils .check_transforms_v2_wrapper (self )
1670-
16711647
16721648class KittiTestCase (datasets_utils .ImageDatasetTestCase ):
16731649 DATASET_CLASS = datasets .Kitti
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