def get_special_tokens_mask(self,
                                token_ids_0,
                                token_ids_1=None,
                                already_has_special_tokens=False):
        """
        Retrieves sequence ids from a token list that has no special tokens added. This method is called when adding
        special tokens using the tokenizer ``encode`` methods.

        Args:
            token_ids_0 (List[int]):
                A list of `inputs_ids` for the first sequence.
            token_ids_1 (List[int], optinal):
                Optional second list of IDs for sequence pairs. Defaults to None.
            already_has_special_tokens (bool, optional): Whether or not the token list is already
                formatted with special tokens for the model. Defaults to None.

        Returns:
            List[int]: The list of integers either be 0 or 1: 1 for a special token, 0 for a sequence token.
        """

        if already_has_special_tokens:
            if token_ids_1 is not None:
                raise ValueError(
                    "You should not supply a second sequence if the provided sequence of "
                    "ids is already formatted with special tokens for the model."
                )
            return list(
                map(lambda x: 1 if x in [self.sep_token_id, self.cls_token_id] else 0,
                    token_ids_0))

        if token_ids_1 is not None:
            return [1] + ([0] * len(token_ids_0)) + [1] + (
                    [0] * len(token_ids_1)) + [1]
        return [1] + ([0] * len(token_ids_0)) + [1]

        Retrieves sequence ids from a token list that has no special tokens added. This method is called when adding
        special tokens using the tokenizer ``encode`` methods.

        Args:
            token_ids_0 (List[int]):
                A list of `inputs_ids` for the first sequence.
            token_ids_1 (List[int], optinal):
                Optional second list of IDs for sequence pairs. Defaults to None.
            already_has_special_tokens (bool, optional): Whether or not the token list is already
                formatted with special tokens for the model. Defaults to None.

        Returns:
            List[int]: The list of integers either be 0 or 1: 1 for a special token, 0 for a sequence token.
        
ptstructure/vqa/pytorchnlp/transformers/bert/tokenizer.py