加了一个def后代码一直在循环run

#………………省略
#text = [list(np.arange(0, y)) for y in n_word]

class yy:
    def weibo_lda(self):
        #text = self.result()
        dictionary = Dictionary(text)
        corpus = [dictionary.doc2bow(tmp) for tmp in text]
        return dictionary, corpus
    def choose_topic(self):
        dictionary, corpus = self.weibo_lda()
        texts = text
        for i in range(1,6):
            print('目前的topic个数:{}'.format(i))
            print('目前的数据量:{}'.format(len(texts)))
            temp = 'lda_{}_{}'.format(i,len(texts))
            tmp = gensim.models.ldamodel.LdaModel(corpus, num_topics=i, id2word=dictionary, passes=20)
            file_path = './{}.model'.format(temp)
            tmp.save(file_path)
            print('------------------')
        #返回topic_num, data_num的值
        return 6,len(texts)
    def perplexity_visible_model(self, topic_num, data_num):
        # texts = self.fenci_data()
        _, corpus = self.weibo_lda()
        x_list = []
        y_list = []
        for i in range(1,topic_num):
            model_name = './lda_{}_{}.model'.format(i, data_num)
            try:
                lda = gensim.models.ldamodel.LdaModel.load(model_name)
                perplexity = lda.log_perplexity(corpus)
                print(perplexity)
                x_list.append(i)
                y_list.append(perplexity)
            except Exception as e:
                print(e)
        plt.xlabel('num topics')
        plt.ylabel('perplexity score')
        plt.legend(('perplexity_values'), loc='best')
        plt.plot(x_list,y_list)
        plt.show()
    def visible_model(self, topic_num, data_num):
        dictionary, _ = self.weibo_lda()
        #texts = self.fenci_data()
        texts = text
        x_list = []
        y_list = []
        for i in range(1,topic_num):
            model_name = './lda_{}_{}.model'.format(i, data_num)
            try:
                lda = gensim.models.ldamodel.LdaModel.load(model_name)
                cv_tmp = CoherenceModel(model=lda, texts=texts, dictionary=dictionary, coherence='c_v')
                x_list.append(i)
                y_list.append(cv_tmp.get_coherence())
            except:
                print('没有这个模型:{}'.format(model_name))
        plt.plot(x_list, y_list)
        plt.xlabel('num topics')
        plt.ylabel('coherence score')
        plt.legend(('coherence_values'), loc='best')
        plt.plot(x_list,y_list)
        plt.show()
if __name__=='__main__':
    t = yy()
    #调用
    topic_num, data_num = t.choose_topic()
    t.perplexity_visible_model(topic_num, data_num)
    t.visible_model(topic_num, data_num)

为什么run出def perplexity_visible_model以后，就会一直循环跑class前面的代码好多次，且visible_model没有算出来？
（加了def visible_model(self, topic_num, data_num):之后才会这样的，删了这个函数就一切正常）

“循环跑class前面的代码好多次 ” 是什么意思，这里循环？