Add common properties input_embeddings and output_embeddings

transformers/modeling_roberta.py

@@ -169,6 +169,10 @@ class RobertaModel(BertModel):
         self.embeddings = RobertaEmbeddings(config)
         self.init_weights()
 
+    @property
+    def input_embeddings(self):
+        return self.embeddings.word_embeddings
+
 
 @add_start_docstrings("""RoBERTa Model with a `language modeling` head on top. """,
     ROBERTA_START_DOCSTRING, ROBERTA_INPUTS_DOCSTRING)
@@ -213,13 +217,10 @@ class RobertaForMaskedLM(BertPreTrainedModel):
         self.lm_head = RobertaLMHead(config)
 
         self.init_weights()
-        self.tie_weights()
 
-    def tie_weights(self):
-        """ Make sure we are sharing the input and output embeddings.
-            Export to TorchScript can't handle parameter sharing so we are cloning them instead.
-        """
-        self._tie_or_clone_weights(self.lm_head.decoder, self.roberta.embeddings.word_embeddings)
+    @property
+    def output_embeddings(self):
+        return self.lm_head.decoder
 
     def forward(self, input_ids, attention_mask=None, token_type_ids=None, position_ids=None, head_mask=None,
                 masked_lm_labels=None):