Update forward signature test for vision models (#27681)

* Update forward signature

* Empty-Commit

tests/models/maskformer/test_modeling_maskformer_swin.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch MaskFormer Swin model. """
 
 import collections
-import inspect
 import unittest
 from typing import Dict, List, Tuple
 
@@ -234,18 +233,6 @@ class MaskFormerSwinModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.Te
             x = model.get_output_embeddings()
             self.assertTrue(x is None or isinstance(x, nn.Linear))
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     @unittest.skip(reason="MaskFormerSwin is only used as backbone and doesn't support output_attentions")
     def test_attention_outputs(self):
         pass

tests/models/mgp_str/test_modeling_mgp_str.py

@@ -14,7 +14,6 @@
 # limitations under the License.
 """ Testing suite for the PyTorch MGP-STR model. """
 
-import inspect
 import unittest
 
 import requests
@@ -151,18 +150,6 @@ class MgpstrModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
             x = model.get_output_embeddings()
             self.assertTrue(x is None or isinstance(x, nn.Linear))
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     @unittest.skip(reason="MgpstrModel does not support feedforward chunking")
     def test_feed_forward_chunking(self):
         pass

tests/models/mobilenet_v1/test_modeling_mobilenet_v1.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch MobileNetV1 model. """
 
 
-import inspect
 import unittest
 
 from transformers import MobileNetV1Config
@@ -177,18 +176,6 @@ class MobileNetV1ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
     def test_attention_outputs(self):
         pass
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_model(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*config_and_inputs)

tests/models/mobilenet_v2/test_modeling_mobilenet_v2.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch MobileNetV2 model. """
 
 
-import inspect
 import unittest
 
 from transformers import MobileNetV2Config
@@ -228,18 +227,6 @@ class MobileNetV2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
     def test_attention_outputs(self):
         pass
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_model(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*config_and_inputs)

tests/models/mobilevit/test_modeling_mobilevit.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch MobileViT model. """
 
 
-import inspect
 import unittest
 
 from transformers import MobileViTConfig
@@ -221,18 +220,6 @@ class MobileViTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCas
     def test_attention_outputs(self):
         pass
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_model(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*config_and_inputs)

tests/models/mobilevitv2/test_modeling_mobilevitv2.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch MobileViTV2 model. """
 
 
-import inspect
 import unittest
 
 from transformers import MobileViTV2Config
@@ -228,18 +227,6 @@ class MobileViTV2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
     def test_multi_gpu_data_parallel_forward(self):
         pass
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_model(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*config_and_inputs)

tests/models/nat/test_modeling_nat.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch Nat model. """
 
 import collections
-import inspect
 import unittest
 
 from transformers import NatConfig
@@ -261,18 +260,6 @@ class NatModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
             x = model.get_output_embeddings()
             self.assertTrue(x is None or isinstance(x, nn.Linear))
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_attention_outputs(self):
         self.skipTest("Nat's attention operation is handled entirely by NATTEN.")
 

tests/models/poolformer/test_modeling_poolformer.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch PoolFormer model. """
 
 
-import inspect
 import unittest
 
 from transformers import is_torch_available, is_vision_available
@@ -208,18 +207,6 @@ class PoolFormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCa
             loss = model(**inputs).loss
             loss.backward()
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     @slow
     def test_model_from_pretrained(self):
         for model_name in POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

tests/models/pvt/test_modeling_pvt.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch Pvt model. """
 
 
-import inspect
 import unittest
 
 from transformers import is_torch_available, is_vision_available
@@ -253,18 +252,6 @@ class PvtModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
             loss = model(**inputs).loss
             loss.backward()
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     @slow
     def test_model_from_pretrained(self):
         for model_name in PVT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

tests/models/regnet/test_modeling_regnet.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch RegNet model. """
 
 
-import inspect
 import unittest
 
 from transformers import RegNetConfig
@@ -161,18 +160,6 @@ class RegNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     def test_model_common_attributes(self):
         pass
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_model(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*config_and_inputs)

tests/models/resnet/test_modeling_resnet.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch ResNet model. """
 
 
-import inspect
 import unittest
 
 from transformers import ResNetConfig
@@ -206,18 +205,6 @@ class ResNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     def test_model_common_attributes(self):
         pass
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_model(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*config_and_inputs)

tests/models/sam/test_modeling_sam.py

@@ -16,7 +16,6 @@
 
 
 import gc
-import inspect
 import unittest
 
 import requests
@@ -338,18 +337,6 @@ class SamModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
             x = model.get_output_embeddings()
             self.assertTrue(x is None or isinstance(x, nn.Linear))
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_model(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*config_and_inputs)

tests/models/segformer/test_modeling_segformer.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch SegFormer model. """
 
 
-import inspect
 import unittest
 
 from transformers import SegformerConfig, is_torch_available, is_vision_available
@@ -212,18 +211,6 @@ class SegformerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCas
     def test_model_common_attributes(self):
         pass
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_attention_outputs(self):
         config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
         config.return_dict = True

tests/models/swiftformer/test_modeling_swiftformer.py

@@ -16,7 +16,6 @@
 
 
 import copy
-import inspect
 import unittest
 
 from transformers import PretrainedConfig, SwiftFormerConfig
@@ -177,18 +176,6 @@ class SwiftFormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
             x = model.get_output_embeddings()
             self.assertTrue(x is None or isinstance(x, nn.Linear))
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_model(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*config_and_inputs)

tests/models/swin/test_modeling_swin.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch Swin model. """
 
 import collections
-import inspect
 import unittest
 
 from transformers import SwinConfig
@@ -300,18 +299,6 @@ class SwinModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
             x = model.get_output_embeddings()
             self.assertTrue(x is None or isinstance(x, nn.Linear))
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_attention_outputs(self):
         config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
         config.return_dict = True

tests/models/swin2sr/test_modeling_swin2sr.py

@@ -13,7 +13,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """ Testing suite for the PyTorch Swin2SR model. """
-import inspect
 import unittest
 
 from transformers import Swin2SRConfig
@@ -232,18 +231,6 @@ class Swin2SRModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
             x = model.get_output_embeddings()
             self.assertTrue(x is None or isinstance(x, nn.Linear))
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     @slow
     def test_model_from_pretrained(self):
         for model_name in SWIN2SR_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

tests/models/swinv2/test_modeling_swinv2.py

@@ -14,7 +14,6 @@
 # limitations under the License.
 """ Testing suite for the PyTorch Swinv2 model. """
 import collections
-import inspect
 import unittest
 
 from transformers import Swinv2Config
@@ -220,18 +219,6 @@ class Swinv2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
             x = model.get_output_embeddings()
             self.assertTrue(x is None or isinstance(x, nn.Linear))
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_attention_outputs(self):
         config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
         config.return_dict = True

tests/models/timesformer/test_modeling_timesformer.py

@@ -16,7 +16,6 @@
 
 
 import copy
-import inspect
 import unittest
 
 import numpy as np
@@ -204,18 +203,6 @@ class TimesformerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
             x = model.get_output_embeddings()
             self.assertTrue(x is None or isinstance(x, nn.Linear))
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_model(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*config_and_inputs)

tests/models/upernet/test_modeling_upernet.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch UperNet framework. """
 
 
-import inspect
 import unittest
 
 from huggingface_hub import hf_hub_download
@@ -170,18 +169,6 @@ class UperNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
     def create_and_test_config_common_properties(self):
         return
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_for_semantic_segmentation(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_semantic_segmentation(*config_and_inputs)

tests/models/videomae/test_modeling_videomae.py

@@ -16,7 +16,6 @@
 
 
 import copy
-import inspect
 import unittest
 
 import numpy as np
@@ -228,18 +227,6 @@ class VideoMAEModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
             x = model.get_output_embeddings()
             self.assertTrue(x is None or isinstance(x, nn.Linear))
 
-    def test_forward_signature(self):
-        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
-
-        for model_class in self.all_model_classes:
-            model = model_class(config)
-            signature = inspect.signature(model.forward)
-            # signature.parameters is an OrderedDict => so arg_names order is deterministic
-            arg_names = [*signature.parameters.keys()]
-
-            expected_arg_names = ["pixel_values"]
-            self.assertListEqual(arg_names[:1], expected_arg_names)
-
     def test_model(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*config_and_inputs)