where do i implement this type?
Actually I have
databunch = BertDataBunch.from_df(".", train, val, test,
                  tokenizer=fastai_tokenizer,
                  vocab=fastai_bert_vocab,
                  text_cols="comment_text",
                  label_cols=label_cols,
                  bs=config.bs,
                  collate_fn=partial(pad_collate, pad_first=False, pad_idx=0),
             )

class FastAiBertTokenizer(BaseTokenizer):
    """Wrapper around BertTokenizer to be compatible with fast.ai"""
    def __init__(self, tokenizer: BertTokenizer, max_seq_len: int=128, **kwargs):
        self._pretrained_tokenizer = tokenizer
        self.max_seq_len = max_seq_len

    def __call__(self, *args, **kwargs):
        return self

    def tokenizer(self, t:str) -> List[str]:
        """Limits the maximum sequence length"""
        return ["[CLS]"] + self._pretrained_tokenizer.tokenize(t)[:self.max_seq_len - 2] + ["[SEP]"]

Do I need to implement this code in tokenizer?
Then how?