Update forward signature test for vision models (#27681)

* Update forward signature

* Empty-Commit

tests/models/beit/test_modeling_beit.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch BEiT model. """
 
 
-import inspect
 import unittest
 
 from datasets import load_dataset
@@ -236,18 +235,6 @@ class BeitModelTest(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/bit/test_modeling_bit.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch Bit model. """
 
 
-import inspect
 import unittest
 
 from transformers import BitConfig
@@ -202,18 +201,6 @@ class BitModelTest(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/convnext/test_modeling_convnext.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch ConvNext model. """
 
 
-import inspect
 import unittest
 
 from transformers import ConvNextConfig
@@ -212,18 +211,6 @@ class ConvNextModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
     def test_feed_forward_chunking(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/convnextv2/test_modeling_convnextv2.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch ConvNextV2 model. """
 
 
-import inspect
 import unittest
 
 from transformers import ConvNextV2Config
@@ -265,18 +264,6 @@ class ConvNextV2ModelTest(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)
-
     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/cvt/test_modeling_cvt.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch CvT model. """
 
 
-import inspect
 import unittest
 from math import floor
 
@@ -191,18 +190,6 @@ class CvtModelTest(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/data2vec/test_modeling_data2vec_vision.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch Data2VecVision model. """
 
 
-import inspect
 import unittest
 
 from transformers import Data2VecVisionConfig
@@ -220,18 +219,6 @@ class Data2VecVisionModelTest(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)
-
     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/deit/test_modeling_deit.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch DeiT model. """
 
 
-import inspect
 import unittest
 import warnings
 
@@ -238,18 +237,6 @@ class DeiTModelTest(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/dinat/test_modeling_dinat.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch Dinat model. """
 
 import collections
-import inspect
 import unittest
 
 from transformers import DinatConfig
@@ -264,18 +263,6 @@ class DinatModelTest(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("Dinat's attention operation is handled entirely by NATTEN.")
 

tests/models/dinov2/test_modeling_dinov2.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch Dinov2 model. """
 
 
-import inspect
 import unittest
 
 from transformers import Dinov2Config
@@ -265,18 +264,6 @@ class Dinov2ModelTest(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/donut/test_modeling_donut_swin.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch Donut Swin model. """
 
 import collections
-import inspect
 import unittest
 
 from transformers import DonutSwinConfig
@@ -186,18 +185,6 @@ class DonutSwinModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCas
             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/dpt/test_modeling_dpt.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch DPT model. """
 
 
-import inspect
 import unittest
 
 from transformers import DPTConfig
@@ -195,18 +194,6 @@ class DPTModelTest(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/dpt/test_modeling_dpt_auto_backbone.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch DPT model. """
 
 
-import inspect
 import unittest
 
 from transformers import Dinov2Config, DPTConfig
@@ -154,18 +153,6 @@ class DPTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     def test_inputs_embeds(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_for_depth_estimation(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_depth_estimation(*config_and_inputs)

tests/models/dpt/test_modeling_dpt_hybrid.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch DPT model. """
 
 
-import inspect
 import unittest
 
 from transformers import DPTConfig
@@ -209,18 +208,6 @@ class DPTModelTest(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/efficientformer/test_modeling_efficientformer.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch EfficientFormer model. """
 
 
-import inspect
 import unittest
 import warnings
 from typing import List
@@ -223,18 +222,6 @@ class EfficientFormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.T
     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_hidden_states_output(self):
         def check_hidden_states_output(inputs_dict, config, model_class):
             model = model_class(config)

tests/models/efficientnet/test_modeling_efficientnet.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch EfficientNet model. """
 
 
-import inspect
 import unittest
 
 from transformers import EfficientNetConfig
@@ -172,18 +171,6 @@ class EfficientNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.Test
     def test_feed_forward_chunking(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/focalnet/test_modeling_focalnet.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch FocalNet model. """
 
 import collections
-import inspect
 import unittest
 
 from transformers import FocalNetConfig
@@ -299,18 +298,6 @@ class FocalNetModelTest(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[:-1]:
-            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 check_hidden_states_output(self, inputs_dict, config, model_class, image_size):
         model = model_class(config)
         model.to(torch_device)

tests/models/glpn/test_modeling_glpn.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch GLPN model. """
 
 
-import inspect
 import unittest
 
 from transformers import is_torch_available, is_vision_available
@@ -177,18 +176,6 @@ class GLPNModelTest(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_attention_outputs(self):
         config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
         config.return_dict = True

tests/models/levit/test_modeling_levit.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch LeViT model. """
 
 
-import inspect
 import unittest
 import warnings
 from math import ceil, floor
@@ -218,18 +217,6 @@ class LevitModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     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_hidden_states_output(self):
         def check_hidden_states_output(inputs_dict, config, model_class):
             model = model_class(config)

tests/models/mask2former/test_modeling_mask2former.py

@@ -14,7 +14,6 @@
 # limitations under the License.
 """ Testing suite for the PyTorch Mask2Former model. """
 
-import inspect
 import unittest
 
 import numpy as np
@@ -242,18 +241,6 @@ class Mask2FormerModelTest(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)
-
     @slow
     def test_model_from_pretrained(self):
         for model_name in ["facebook/mask2former-swin-small-coco-instance"]:

tests/models/maskformer/test_modeling_maskformer.py

@@ -15,7 +15,6 @@
 """ Testing suite for the PyTorch MaskFormer model. """
 
 import copy
-import inspect
 import unittest
 
 import numpy as np
@@ -266,18 +265,6 @@ class MaskFormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCa
     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)
-
     @slow
     def test_model_from_pretrained(self):
         for model_name in ["facebook/maskformer-swin-small-coco"]: