def set_special_tokens(self, special_tokens):
        """ Add a list of additional tokens to the encoder.
            The additional tokens are indexed starting from the last index of the
            current vocabulary in the order of the `special_tokens` list.
        """
        if not special_tokens:
            self.special_tokens = {}
            self.special_tokens_decoder = {}
            return
        self.special_tokens = dict((tok, len(self.encoder) + i)
                                   for i, tok in enumerate(special_tokens))
        self.special_tokens_decoder = {v: k for k, v in self.special_tokens.items()}
        logger.info("Special tokens {}".format(self.special_tokens))
 Add a list of additional tokens to the encoder.
            The additional tokens are indexed starting from the last index of the
            current vocabulary in the order of the `special_tokens` list.
        
training/DeepSpeed-Domino/megatron/tokenizer/gpt2_tokenization.py