How to use the pythainlp.ulmfit.utils.ThaiTokenizer function in pythainlp

def proc_all_mp(ss):
        """
        :meth: `proc_all` runs `proc_text` for multiple sentences using multiple cpus
        :param str text: text to process
        :return: processed and tokenized text
        """
        ncpus = num_cpus() // 2
        with ProcessPoolExecutor(ncpus) as e:
            return sum(e.map(ThaiTokenizer.proc_all, ss), [])

def get_texts(df):
    """
    :meth: `get_texts` get tuple of tokenized texts and labels
    :param pandas.DataFrame df: `pandas.DataFrame` with `label` as first column and `text` as second column
    :return:
        * tok - lists of tokenized texts with beginning-of-sentence tag `xbos` as first element of each list
        * labels - list of labels
    """
    labels = df.iloc[:, 0].values.astype(np.int64)
    texts = BOS + df.iloc[:, 1].astype(str).apply(lambda x: x.rstrip())
    tok = ThaiTokenizer().proc_all_mp(partition_by_cores(texts))
    return (tok, list(labels))

def proc_all(ss):
        """
        :meth: `proc_all` runs `proc_text` for multiple sentences
        :param str text: text to process
        :return: processed and tokenized text
        """
        tok = ThaiTokenizer()
        return [tok.proc_text(s) for s in ss]

def proc_text(self, text):
        """
        :meth: `proc_text` procss and tokenize text removing repetitions, special characters, double spaces
        :param str text: text to process
        :return: processed and tokenized text
        """
        s = self.__RE_REP.sub(ThaiTokenizer.replace_rep, text)
        s = self.__RE_SLASH_HASH.sub(r" \1 ", s)
        s = self.__RE_DOUBLE_SPACE(" ", s)
        return self.tokenize(s)