老师，我这出的结果和您的不一样。

def get_train_data(input_file):
    """
    get train data for LFM model train
    Args:
        input_file:user item rating file
    Return:
        a list:[(userid, itemid, label), (userid1, itemid1, label)]
    """
    if not os.path.exists(input_file):
        return[]
    score_dict = get_ave_score(input_file)
    neg_dict = {}
    pos_dict = {}
    train_data = []
    linenum = 0
    score_thr = 4.0
    fp = open(input_file)
    for line in fp:
        if linenum == 0:
            linenum += 1
            continue
        item = line.strip().split(',')
        if len(item) < 4:
            continue
        userid, itemid, rating = item[0], item[1], float(item[2])
        if userid not in pos_dict:
            pos_dict[userid] = []
        if userid not in neg_dict:
            neg_dict[userid] = []
        if rating >= score_thr:
            pos_dict[userid].append((itemid, 1))
        else:
            score = score_dict.get(itemid, 0)
            neg_dict[userid].append((itemid, score))
    fp.close()
    for userid in pos_dict:
        data_num = min(len(pos_dict[userid]), len(neg_dict.get(userid, [])))
        if data_num > 0:
            train_data += [(userid, zuhe[0], zuhe[1]) for zuhe in pos_dict[userid]][:data_num]
        else:
            continue
        sorted_neg_list = sorted(neg_dict[userid], key=lambda element:element[1], reverse=True)[:data_num]
        train_data += [(userid, zuhe[0], 0) for zuhe in sorted_neg_list]
    return train_data

if __name__ == "__main__":
    train_data = get_train_data("../data/ratings.txt")
    print(len(train_data))
    print(train_data[:20])