Enable more test_torchscript (#16679)

* update _create_and_check_torchscript

* Enable test_torchscript

* clear_class_registry
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

tests/beit/test_modeling_beit.py

@@ -192,7 +192,6 @@ class BeitModelTest(ModelTesterMixin, unittest.TestCase):
     )
 
     test_pruning = False
-    test_torchscript = False
     test_resize_embeddings = False
     test_head_masking = False
 

tests/canine/test_modeling_canine.py

@@ -219,7 +219,6 @@ class CanineModelTest(ModelTesterMixin, unittest.TestCase):
         else ()
     )
 
-    test_torchscript = False
     test_mismatched_shapes = False
     test_resize_embeddings = False
     test_pruning = False

tests/clip/test_modeling_clip.py

@@ -151,7 +151,6 @@ class CLIPVisionModelTest(ModelTesterMixin, unittest.TestCase):
     all_model_classes = (CLIPVisionModel,) if is_torch_available() else ()
 
     test_pruning = False
-    test_torchscript = False
     test_resize_embeddings = False
     test_head_masking = False
 

tests/convnext/test_modeling_convnext.py

@@ -138,7 +138,6 @@ class ConvNextModelTest(ModelTesterMixin, unittest.TestCase):
     )
 
     test_pruning = False
-    test_torchscript = False
     test_resize_embeddings = False
     test_head_masking = False
     has_attentions = False

tests/ctrl/test_modeling_ctrl.py

@@ -174,7 +174,6 @@ class CTRLModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
     all_model_classes = (CTRLModel, CTRLLMHeadModel, CTRLForSequenceClassification) if is_torch_available() else ()
     all_generative_model_classes = (CTRLLMHeadModel,) if is_torch_available() else ()
     test_pruning = True
-    test_torchscript = False
     test_resize_embeddings = False
     test_head_masking = False
 

tests/data2vec/test_modeling_data2vec_audio.py

@@ -372,7 +372,6 @@ class Data2VecAudioModelTest(ModelTesterMixin, unittest.TestCase):
     )
     test_pruning = False
     test_headmasking = False
-    test_torchscript = False
 
     def setUp(self):
         self.model_tester = Data2VecAudioModelTester(self)

tests/decision_transformer/test_modeling_decision_transformer.py

@@ -148,6 +148,7 @@ class DecisionTransformerModelTest(ModelTesterMixin, GenerationTesterMixin, unit
     test_inputs_embeds = False
     test_model_common_attributes = False
     test_gradient_checkpointing = False
+    test_torchscript = False
 
     def setUp(self):
         self.model_tester = DecisionTransformerModelTester(self)

tests/deit/test_modeling_deit.py

@@ -169,7 +169,6 @@ class DeiTModelTest(ModelTesterMixin, unittest.TestCase):
     )
 
     test_pruning = False
-    test_torchscript = False
     test_resize_embeddings = False
     test_head_masking = False
 

tests/distilbert/test_modeling_distilbert.py

@@ -211,7 +211,6 @@ class DistilBertModelTest(ModelTesterMixin, unittest.TestCase):
     )
     fx_compatible = True
     test_pruning = True
-    test_torchscript = True
     test_resize_embeddings = True
     test_resize_position_embeddings = True
 

tests/dpt/test_modeling_dpt.py

@@ -154,7 +154,6 @@ class DPTModelTest(ModelTesterMixin, unittest.TestCase):
     all_model_classes = (DPTModel, DPTForDepthEstimation, DPTForSemanticSegmentation) if is_torch_available() else ()
 
     test_pruning = False
-    test_torchscript = False
     test_resize_embeddings = False
     test_head_masking = False
 

tests/fnet/test_modeling_fnet.py

@@ -284,7 +284,6 @@ class FNetModelTest(ModelTesterMixin, unittest.TestCase):
 
     # Skip Tests
     test_pruning = False
-    test_torchscript = False
     test_head_masking = False
     test_pruning = False
 

tests/glpn/test_modeling_glpn.py

@@ -150,7 +150,6 @@ class GLPNModelTest(ModelTesterMixin, unittest.TestCase):
     test_head_masking = False
     test_pruning = False
     test_resize_embeddings = False
-    test_torchscript = False
 
     def setUp(self):
         self.model_tester = GLPNModelTester(self)

tests/hubert/test_modeling_hubert.py

@@ -300,7 +300,6 @@ class HubertModelTest(ModelTesterMixin, unittest.TestCase):
     all_model_classes = (HubertForCTC, HubertForSequenceClassification, HubertModel) if is_torch_available() else ()
     test_pruning = False
     test_headmasking = False
-    test_torchscript = False
 
     def setUp(self):
         self.model_tester = HubertModelTester(self)
@@ -445,7 +444,6 @@ class HubertRobustModelTest(ModelTesterMixin, unittest.TestCase):
     all_model_classes = (HubertForCTC, HubertForSequenceClassification, HubertModel) if is_torch_available() else ()
     test_pruning = False
     test_headmasking = False
-    test_torchscript = False
 
     def setUp(self):
         self.model_tester = HubertModelTester(

tests/maskformer/test_modeling_maskformer.py

@@ -177,7 +177,6 @@ class MaskFormerModelTest(ModelTesterMixin, unittest.TestCase):
     all_model_classes = (MaskFormerModel, MaskFormerForInstanceSegmentation) if is_torch_available() else ()
 
     is_encoder_decoder = False
-    test_torchscript = False
     test_pruning = False
     test_head_masking = False
     test_missing_keys = False

tests/mpnet/test_modeling_mpnet.py

@@ -205,7 +205,6 @@ class MPNetModelTest(ModelTesterMixin, unittest.TestCase):
         else ()
     )
     test_pruning = False
-    test_torchscript = True
     test_resize_embeddings = True
 
     def setUp(self):

tests/prophetnet/test_modeling_prophetnet.py

@@ -890,7 +890,6 @@ class ProphetNetModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.Test
     all_model_classes = (ProphetNetModel, ProphetNetForConditionalGeneration) if is_torch_available() else ()
     all_generative_model_classes = (ProphetNetForConditionalGeneration,) if is_torch_available() else ()
     test_pruning = False
-    test_torchscript = False
     test_resize_embeddings = False
     is_encoder_decoder = True
 
@@ -1100,7 +1099,7 @@ class ProphetNetStandaloneDecoderModelTest(ModelTesterMixin, GenerationTesterMix
     all_model_classes = (ProphetNetDecoder, ProphetNetForCausalLM) if is_torch_available() else ()
     all_generative_model_classes = (ProphetNetForCausalLM,) if is_torch_available() else ()
     test_pruning = False
-    test_torchscript = False
+
     test_resize_embeddings = False
     is_encoder_decoder = False
 
@@ -1128,7 +1127,7 @@ class ProphetNetStandaloneDecoderModelTest(ModelTesterMixin, GenerationTesterMix
 class ProphetNetStandaloneEncoderModelTest(ModelTesterMixin, unittest.TestCase):
     all_model_classes = (ProphetNetEncoder,) if is_torch_available() else ()
     test_pruning = False
-    test_torchscript = False
+
     test_resize_embeddings = False
     is_encoder_decoder = False
 

tests/regnet/test_modeling_regnet.py

@@ -127,7 +127,6 @@ class RegNetModelTest(ModelTesterMixin, unittest.TestCase):
     all_model_classes = (RegNetModel, RegNetForImageClassification) if is_torch_available() else ()
 
     test_pruning = False
-    test_torchscript = False
     test_resize_embeddings = False
     test_head_masking = False
     has_attentions = False

tests/resnet/test_modeling_resnet.py

@@ -127,7 +127,6 @@ class ResNetModelTest(ModelTesterMixin, unittest.TestCase):
     all_model_classes = (ResNetModel, ResNetForImageClassification) if is_torch_available() else ()
 
     test_pruning = False
-    test_torchscript = False
     test_resize_embeddings = False
     test_head_masking = False
     has_attentions = False

tests/segformer/test_modeling_segformer.py

@@ -165,7 +165,6 @@ class SegformerModelTest(ModelTesterMixin, unittest.TestCase):
     test_head_masking = False
     test_pruning = False
     test_resize_embeddings = False
-    test_torchscript = False
 
     def setUp(self):
         self.model_tester = SegformerModelTester(self)

tests/sew/test_modeling_sew.py

@@ -303,7 +303,6 @@ class SEWModelTest(ModelTesterMixin, unittest.TestCase):
     all_model_classes = (SEWForCTC, SEWModel, SEWForSequenceClassification) if is_torch_available() else ()
     test_pruning = False
     test_headmasking = False
-    test_torchscript = False
 
     def setUp(self):
         self.model_tester = SEWModelTester(self)