':key: å©çšç°ææš¡åæšæ­æ°æ®
:param article_list: æ¯äžè¡çæ°æ®æ ŒåŒäžº: id[tab]word1 word2 word3......
:param iters_num: æ¯äžæ¬¡è¿­ä»£çæ¬¡æ°
:param repeat_num: éå€è¿­ä»£çæ¬¡æ°'

def inference_data(self, article_list, iters_num=100, repeat_num=3):

    self.init_corpus_with_articles(article_list)
    return_theta = numpy.zeros((self.M, self.K))
    for i in range(repeat_num):
        logging.debug(('inference    repeat_num:    ' + str((i + 1))))
        self.current_iter = 0
        self.iters_num = iters_num
        self.Z = [[numpy.random.randint(self.K) for n in range(len(self.arts_Z[m]))] for m in range(self.M)]
        self.init_statistics()
        self.gibbs_sampling(is_calculate_preplexity=False)
        self.calculate_theta()
        return_theta += self.theta
    return (return_theta / repeat_num)
