Rename test_model_common_attributes -> test_model_get_set_embeddings (#31321)

* Rename to test_model_common_attributes
The method name is misleading - it is testing being able to get and set embeddings, not common attributes to all models

* Explicitly skip

tests/models/wav2vec2/test_modeling_wav2vec2.py

@@ -567,7 +567,7 @@ class Wav2Vec2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
     # Wav2Vec2 has no inputs_embeds
     # and thus the `get_input_embeddings` fn
     # is not implemented
-    def test_model_common_attributes(self):
+    def test_model_get_set_embeddings(self):
         pass
 
     @is_pt_flax_cross_test
@@ -921,7 +921,7 @@ class Wav2Vec2RobustModelTest(ModelTesterMixin, unittest.TestCase):
     # Wav2Vec2 has no inputs_embeds
     # and thus the `get_input_embeddings` fn
     # is not implemented
-    def test_model_common_attributes(self):
+    def test_model_get_set_embeddings(self):
         pass
 
     def test_retain_grad_hidden_states_attentions(self):

tests/models/wav2vec2_bert/test_modeling_wav2vec2_bert.py

@@ -557,7 +557,7 @@ class Wav2Vec2BertModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.Test
 
     # Ignore copy
     @unittest.skip(reason="Wav2Vec2Bert has no inputs_embeds")
-    def test_model_common_attributes(self):
+    def test_model_get_set_embeddings(self):
         pass
 
     # Ignore copy

tests/models/wav2vec2_conformer/test_modeling_wav2vec2_conformer.py

@@ -528,7 +528,7 @@ class Wav2Vec2ConformerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest
     # Wav2Vec2Conformer has no inputs_embeds
     # and thus the `get_input_embeddings` fn
     # is not implemented
-    def test_model_common_attributes(self):
+    def test_model_get_set_embeddings(self):
         pass
 
     @is_pt_flax_cross_test

tests/models/wavlm/test_modeling_wavlm.py

@@ -387,7 +387,7 @@ class WavLMModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     # WavLM has no inputs_embeds
     # and thus the `get_input_embeddings` fn
     # is not implemented
-    def test_model_common_attributes(self):
+    def test_model_get_set_embeddings(self):
         pass
 
     # WavLM uses PyTorch's multi-head-attention class

tests/models/whisper/test_modeling_whisper.py

@@ -3153,7 +3153,7 @@ class WhisperEncoderModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.
             self.assertTrue((outputs_embeds == outputs).all())
 
     # Needs to override as the encoder input embedding is a Conv1d
-    def test_model_common_attributes(self):
+    def test_model_get_set_embeddings(self):
         config, _ = self.model_tester.prepare_config_and_inputs_for_common()
 
         for model_class in self.all_model_classes:

tests/models/x_clip/test_modeling_x_clip.py

@@ -161,7 +161,7 @@ class XCLIPVisionModelTest(ModelTesterMixin, unittest.TestCase):
     def test_inputs_embeds(self):
         pass
 
-    def test_model_common_attributes(self):
+    def test_model_get_set_embeddings(self):
         config, _ = self.model_tester.prepare_config_and_inputs_for_common()
 
         for model_class in self.all_model_classes:
@@ -561,7 +561,7 @@ class XCLIPModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
         pass
 
     @unittest.skip(reason="XCLIPModel does not have input/output embeddings")
-    def test_model_common_attributes(self):
+    def test_model_get_set_embeddings(self):
         pass
 
     @unittest.skip(reason="XCLIPModel does not support feedforward chunking")

tests/models/yolos/test_modeling_yolos.py

@@ -210,7 +210,7 @@ class YolosModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
         # YOLOS does not use inputs_embeds
         pass
 
-    def test_model_common_attributes(self):
+    def test_model_get_set_embeddings(self):
         config, _ = self.model_tester.prepare_config_and_inputs_for_common()
 
         for model_class in self.all_model_classes:

tests/test_modeling_common.py

@@ -1971,13 +1971,17 @@ class ModelTesterMixin:
             # Check that the model can still do a forward pass successfully (every parameter should be resized)
             model(**self._prepare_for_class(inputs_dict, model_class))
 
-    def test_model_common_attributes(self):
+    def test_model_get_set_embeddings(self):
         config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
 
         for model_class in self.all_model_classes:
             model = model_class(config)
             self.assertIsInstance(model.get_input_embeddings(), (nn.Embedding, AdaptiveEmbedding))
-            model.set_input_embeddings(nn.Embedding(10, 10))
+
+            new_input_embedding_layer = nn.Embedding(10, 10)
+            model.set_input_embeddings(new_input_embedding_layer)
+            self.assertEqual(model.get_input_embeddings(), new_input_embedding_layer)
+
             x = model.get_output_embeddings()
             self.assertTrue(x is None or isinstance(x, nn.Linear))