src/transformers/models/fnet/tokenization_fnet_fast.py/FNetTokenizerFast/__init__
class FNetTokenizerFast:    def __init__(
        self,
        vocab_file=None,
        tokenizer_file=None,
        do_lower_case=False,
        remove_space=True,
        keep_accents=True,
        unk_token="<unk>",
        sep_token="[SEP]",
        pad_token="<pad>",
        cls_token="[CLS]",
        mask_token="[MASK]",
        **kwargs,
    ):
        # Mask token behave like a normal word, i.e. include the space before it and
        # is included in the raw text, there should be a match in a non-normalized sentence.
        mask_token = (
            AddedToken(mask_token, lstrip=True, rstrip=False, normalized=False)
            if isinstance(mask_token, str)
            else mask_token
        )

        super().__init__(
            vocab_file,
            tokenizer_file=tokenizer_file,
            do_lower_case=do_lower_case,
            remove_space=remove_space,
            keep_accents=keep_accents,
            unk_token=unk_token,
            sep_token=sep_token,
            pad_token=pad_token,
            cls_token=cls_token,
            mask_token=mask_token,
            **kwargs,
        )

        self.do_lower_case = do_lower_case
        self.remove_space = remove_space
        self.keep_accents = keep_accents
        self.vocab_file = vocab_file
        self.can_save_slow_tokenizer = False if not self.vocab_file else True