[PyTorch] Refactor Resize Token Embeddings (#8880)

* fix resize tokens

* correct mobile_bert

* move embedding fix into modeling_utils.py

* refactor

* fix lm head resize

* refactor

* break lines to make sylvain happy

* add news tests

* fix typo

* improve test

* skip bart-like for now

* check if base_model = get(...) is necessary

* clean files

* improve test

* fix tests

* revert style templates

* Update templates/adding_a_new_model/cookiecutter-template-{{cookiecutter.modelname}}/modeling_{{cookiecutter.lowercase_modelname}}.py

src/transformers/models/roberta/modeling_roberta.py

@@ -752,6 +752,9 @@ class RobertaForCausalLM(RobertaPreTrainedModel):
     def get_output_embeddings(self):
         return self.lm_head.decoder
 
+    def set_output_embeddings(self, new_embeddings):
+        self.lm_head.decoder = new_embeddings
+
     @add_start_docstrings_to_model_forward(ROBERTA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
     @replace_return_docstrings(output_type=CausalLMOutputWithCrossAttentions, config_class=_CONFIG_FOR_DOC)
     def forward(
@@ -873,6 +876,9 @@ class RobertaForMaskedLM(RobertaPreTrainedModel):
     def get_output_embeddings(self):
         return self.lm_head.decoder
 
+    def set_output_embeddings(self, new_embeddings):
+        self.lm_head.decoder = new_embeddings
+
     @add_start_docstrings_to_model_forward(ROBERTA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
     @add_code_sample_docstrings(
         tokenizer_class=_TOKENIZER_FOR_DOC,