How to use the ginza.tag_map.TAG_MAP function in ginza

last_morph = m
                else:
                    last_morph = m
        if last_morph:
            morph_spaces.append((last_morph, False))

        # the last space is removed by JapaneseReviser at the final stage of pipeline
        words = [m.surface() for m, spaces in morph_spaces]
        spaces = [space for m, space in morph_spaces]
        doc = Doc(self.nlp.vocab if self.nlp else Vocab(), words=words, spaces=spaces)
        next_tag = morph_tag(morph_spaces[0][0].part_of_speech()[0:4]) if len(doc) else ''
        for token, (morph, spaces) in zip(doc, morph_spaces):
            tag = next_tag
            next_tag = morph_tag(morph_spaces[token.i + 1][0].part_of_speech()[0:4]) if token.i < len(doc) - 1 else ''
            token.tag_ = tag
            token.pos = TAG_MAP[tag][POS]
            # TODO separate lexical rules to resource files
            if morph.normalized_form() == '為る' and tag == '動詞-非自立可能':
                token.pos_ = 'AUX'
            elif tag == '名詞-普通名詞-サ変可能':
                if next_tag == '動詞-非自立可能':
                    token.pos_ = 'VERB'
            elif tag == '名詞-普通名詞-サ変形状詞可能':
                if next_tag == '動詞-非自立可能':
                    token.pos_ = 'VERB'
                elif next_tag == '助動詞' or next_tag.find('形状詞') >= 0:
                    token.pos_ = 'ADJ'
            token.lemma_ = morph.normalized_form()
            token._.inf = ','.join(morph.part_of_speech()[4:])
            token._.reading = morph.reading_form()
            token._.sudachi = morph
        if self.use_sentence_separator: