Fix embeddings resizing in TF models (#8657)

* Resize the biases in same time than the embeddings

* Trigger CI

* Biases are not reset anymore

* Remove get_output_embeddings + better LM model detection in generation utils

* Apply style

* First test on BERT

* Update docstring + new name

* Apply the new resizing logic to all the models

* fix tests

* Apply style

* Update the template

* Fix naming

* Fix naming

* Apply style

* Apply style

* Remove unused import

* Revert get_output_embeddings

* Trigger CI

* Update num parameters

* Restore get_output_embeddings in TFPretrainedModel and add comments

* Style

* Add decoder resizing

* Style

* Fix tests

* Separate bias and decoder resize

* Fix tests

* Fix tests

* Apply style

* Add bias resizing in MPNet

* Trigger CI

* Apply style

tests/test_modeling_tf_bert.py

@@ -331,6 +331,25 @@ class TFBertModelTest(TFModelTesterMixin, unittest.TestCase):
         model = TFBertModel.from_pretrained("jplu/tiny-tf-bert-random")
         self.assertIsNotNone(model)
 
+    def test_model_common_attributes(self):
+        config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
+        list_lm_models = [TFBertForMaskedLM, TFBertForPreTraining, TFBertLMHeadModel]
+
+        for model_class in self.all_model_classes:
+            model = model_class(config)
+            assert isinstance(model.get_input_embeddings(), tf.keras.layers.Layer)
+
+            if model_class in list_lm_models:
+                x = model.get_output_layer_with_bias()
+                assert isinstance(x, tf.keras.layers.Layer)
+                name = model.get_prefix_bias_name()
+                assert isinstance(name, str)
+            else:
+                x = model.get_output_layer_with_bias()
+                assert x is None
+                name = model.get_prefix_bias_name()
+                assert x is None
+
     def test_custom_load_tf_weights(self):
         model, output_loading_info = TFBertForTokenClassification.from_pretrained(
             "jplu/tiny-tf-bert-random", output_loading_info=True