src/transformers/tokenization_utils_base.py/PreTrainedTokenizerBase/__init__
class PreTrainedTokenizerBase:    def __init__(self, **kwargs):
        # inputs and kwargs for saving and re-loading (see ``from_pretrained`` and ``save_pretrained``)
        self.init_inputs = ()
        self.init_kwargs = copy.deepcopy(kwargs)
        self.name_or_path = kwargs.pop("name_or_path", "")

        # For backward compatibility we fallback to set model_max_length from max_len if provided
        model_max_length = kwargs.pop("model_max_length", kwargs.pop("max_len", None))
        self.model_max_length = model_max_length if model_max_length is not None else VERY_LARGE_INTEGER

        # Padding side is right by default and overridden in subclasses. If specified in the kwargs, it is changed.
        self.padding_side = kwargs.pop("padding_side", self.padding_side)
        assert self.padding_side in [
            "right",
            "left",
        ], f"Padding side should be selected between 'right' and 'left', current value: {self.padding_side}"
        self.model_input_names = kwargs.pop("model_input_names", self.model_input_names)

        self.deprecation_warnings = (
            {}
        )  # Use to store when we have already noticed a deprecation warning (avoid overlogging).

        super().__init__(**kwargs)