src/transformers/models/gptsan_japanese/tokenization_gptsan_japanese.py/GPTSanJapaneseTokenizer/_batch_encode_plus
class GPTSanJapaneseTokenizer:    def _batch_encode_plus(
        self,
        batch_text_or_text_pairs: Union[
            List[TextInput], List[TextInputPair], List[PreTokenizedInput], List[PreTokenizedInputPair]
        ],
        add_special_tokens: bool = True,
        padding_strategy: PaddingStrategy = PaddingStrategy.DO_NOT_PAD,
        truncation_strategy: TruncationStrategy = TruncationStrategy.DO_NOT_TRUNCATE,
        max_length: Optional[int] = None,
        stride: int = 0,
        is_split_into_words: bool = False,
        pad_to_multiple_of: Optional[int] = None,
        return_tensors: Optional[str] = None,
        return_token_type_ids: Optional[bool] = None,
        return_attention_mask: Optional[bool] = None,
        return_overflowing_tokens: bool = False,
        return_special_tokens_mask: bool = False,
        return_offsets_mapping: bool = False,
        return_length: bool = False,
        verbose: bool = True,
    ) -> BatchEncoding:
        # This tokenizer converts input text pairs into Prefix input and subsequent input
        if type(batch_text_or_text_pairs[0]) is tuple or type(batch_text_or_text_pairs[0]) is list:
            # As a single text with an explicit un-prefix position
            batch_prefix_texts = []
            for pref, txt in batch_text_or_text_pairs:
                batch_prefix_texts.append(pref + self.sep_token + txt)
            batch_text_or_text_pairs = batch_prefix_texts

        return super()._batch_encode_plus(
            batch_text_or_text_pairs,
            add_special_tokens,
            padding_strategy,
            truncation_strategy,
            max_length,
            stride,
            is_split_into_words,
            pad_to_multiple_of,
            return_tensors,
            return_token_type_ids,
            return_attention_mask,
            return_overflowing_tokens,
            return_special_tokens_mask,
            return_offsets_mapping,
            return_length,
            verbose,
        )