def prepare_for_tokenization(
        self, text: str, is_split_into_words: bool = False, **kwargs
    ) -> Tuple[str, Dict[str, Any]]:
        """
        Performs any necessary transformations before tokenization.

        This method should pop the arguments from kwargs and return the remaining `kwargs` as well. We test the
        `kwargs` at the end of the encoding process to be sure all the arguments have been used.

        Args:
            text (`str`):
                The text to prepare.
            is_split_into_words (`bool`, *optional*, defaults to `False`):
                Whether or not the input is already pre-tokenized (e.g., split into words). If set to `True`, the
                tokenizer assumes the input is already split into words (for instance, by splitting it on whitespace)
                which it will tokenize. This is useful for NER or token classification.
            kwargs (`Dict[str, Any]`, *optional*):
                Keyword arguments to use for the tokenization.

        Returns:
            `Tuple[str, Dict[str, Any]]`: The prepared text and the unused kwargs.
        """
        return (text, kwargs)

        Performs any necessary transformations before tokenization.

        This method should pop the arguments from kwargs and return the remaining `kwargs` as well. We test the
        `kwargs` at the end of the encoding process to be sure all the arguments have been used.

        Args:
            text (`str`):
                The text to prepare.
            is_split_into_words (`bool`, *optional*, defaults to `False`):
                Whether or not the input is already pre-tokenized (e.g., split into words). If set to `True`, the
                tokenizer assumes the input is already split into words (for instance, by splitting it on whitespace)
                which it will tokenize. This is useful for NER or token classification.
            kwargs (`Dict[str, Any]`, *optional*):
                Keyword arguments to use for the tokenization.

        Returns:
            `Tuple[str, Dict[str, Any]]`: The prepared text and the unused kwargs.
        
dpkd/transformers/src/transformers/tokenization_utils.py