def METHOD_NAME():
    print('Loaded language model: %s' % language_model_path)
    print(sentence_word_split)
    # Show scores and n-gram matches
    words = ['<s>'] + sentence_word_split.split() + ['</s>']
    for i, (prob, length,
            oov) in enumerate(model.full_scores(sentence_word_split)):
        print('{0} {1}: {2}'.format(prob, length, ' '.join(words[i + 2 - length:
                                                                 i + 2])))
        if oov:
            print('\t"{0}" is an OOV'.format(words[i + 1]))
    print("-" * 42)
    # Find out-of-vocabulary words
    oov = []
    for w in words:
        if w not in model:
            print('"{0}" is an OOV'.format(w))
            oov.append(w)
    # zh_giga.no_cna_cmn.prune01244.klm is chinese charactor LM 
    assert oov == ["盘点", "不怕", "网站", "❗", "️", "海淘", "向来", "便宜", "保真",
                   "！"], 'error oov'