RoBERTa doesn't print a warning when no special tokens are passed.

transformers/modeling_roberta.py

@@ -169,18 +169,6 @@ class RobertaModel(BertModel):
         self.embeddings = RobertaEmbeddings(config)
         self.init_weights()
 
-    def forward(self, input_ids, attention_mask=None, token_type_ids=None, position_ids=None, head_mask=None):
-        if input_ids[:, 0].sum().item() != 0:
-            logger.warning("A sequence with no special tokens has been passed to the RoBERTa model. "
-                           "This model requires special tokens in order to work. "
-                           "Please specify add_special_tokens=True in your tokenize.encode()"
-                           "or tokenizer.convert_tokens_to_ids().")
-        return super(RobertaModel, self).forward(input_ids,
-                                                 attention_mask=attention_mask,
-                                                 token_type_ids=token_type_ids,
-                                                 position_ids=position_ids,
-                                                 head_mask=head_mask)
-
 
 @add_start_docstrings("""RoBERTa Model with a `language modeling` head on top. """,
     ROBERTA_START_DOCSTRING, ROBERTA_INPUTS_DOCSTRING)

transformers/modeling_tf_roberta.py

@@ -65,22 +65,6 @@ class TFRobertaMainLayer(TFBertMainLayer):
         super(TFRobertaMainLayer, self).__init__(config, **kwargs)
         self.embeddings = TFRobertaEmbeddings(config, name='embeddings')
 
-    def call(self, inputs, **kwargs):
-        # Check that input_ids starts with control token
-        if isinstance(inputs, (tuple, list)):
-            input_ids = inputs[0]
-        elif isinstance(inputs, dict):
-            input_ids = inputs.get('input_ids')
-        else:
-            input_ids = inputs
-
-        if tf.not_equal(tf.reduce_sum(input_ids[:, 0]), 0):
-            tf.print("A sequence with no special tokens has been passed to the RoBERTa model. "
-                           "This model requires special tokens in order to work. "
-                           "Please specify add_special_tokens=True in your encoding.")
-
-        return super(TFRobertaMainLayer, self).call(inputs, **kwargs)
-
 
 class TFRobertaPreTrainedModel(TFPreTrainedModel):
     """ An abstract class to handle weights initialization and