How to use the tokenizers.MeCabTokenizer function in tokenizers

help='dictionary for MeCab tokenizer')
    parser.add_argument('--mecab_udic', type=str, default=None,
                        help='user dictionary for MeCab tokenizer')
    args = parser.parse_args()

    if args.tokenizer == 'regexp':
        logging.info('tokenizer: RegExpTokenizer')
        tokenizer = tokenizers.RegExpTokenizer(lower=args.lower)
    elif args.tokenizer == 'nltk':
        logging.info('tokenizer: NLTKTokenizer')
        tokenizer = tokenizers.NLTKTokenizer(lower=args.lower)
    elif args.tokenizer == 'mecab':
        logging.info('tokenizer: MeCabTokenizer')
        logging.info(f'dictionary: {args.mecab_dic}')
        logging.info(f'user dictionary: {args.mecab_udic}')
        tokenizer = tokenizers.MeCabTokenizer(
            dic=args.mecab_dic, udic=args.mecab_udic, lower=args.lower)
    else:
        raise Exception('Undefined tokenizer type.')

    logging.info('generating corpus for training')
    n_processed = 0
    with gzip.open(args.cirrus_file, 'rt') as fi, \
         bz2.open(args.out_file, 'wt') as fo:
        for line in fi:
            article = json.loads(line)
            if 'title' not in article:
                continue

            title = article['title']
            text = regex_spaces.sub(r' ', article['text'])

def __init__(self, dic=None, udic=None, lower=False):
        super(MeCabTokenizer, self).__init__(lower)
        import MeCab
        mecab_options = ['-O wakati']
        if dic:
            mecab_options.append(f'-d {dic}')
        if udic:
            mecab_options.append(f'-u {udic}')

        self._mt = MeCab.Tagger(' '.join(mecab_options))