import os
from config import samples_mode
import time

if __name__  == '__main__':

    # 训练召回模型
    # print("**"*10+"build_keywords"+"**"*10)
    # os.system('python ./matching/shixun/build_keywords.py')
    # print("**"*10+"faiss_word2vec"+"**"*10)
    # os.system('python ./matching/shixun/faiss_word2vec.py')
    # print("**"*10+"hnsw_faiss"+"**"*10)
    # os.system('python ./matching/shixun/hnsw_faiss.py')
    # print("**"*10+"item_embedding"+"**"*10)  
    # os.system('python ./matching/shixun/item_embedding.py')
    # print("**"*10+"item_merge_emb"+"**"*10)
    # os.system('python ./matching/shixun/item_merge_emb.py')
    # print("**"*10+"Item2Vec"+"**"*10)
    # os.system('python ./matching/shixun/Item2Vec.py')
    # print("**"*10+"cold_start_recall"+"**"*10)
    # os.system('python ./matching/shixun/cold_start_recall.py')
    # print("**"*10+"item_embedding_recall"+"**"*10)
    # os.system('python ./matching/shixun/item_embedding_recall.py')
    # print("**"*10+"itemcf_recall"+"**"*10)
    # os.system('python ./matching/shixun/itemcf_recall.py')
    # print("**"*10+"youtubednn_recall_train"+"**"*10)   
    # os.system('python ./matching/shixun/youtubednn_recall_train.py')
    # print("**"*10+"youtube_usercf_recall"+"**"*10)    
    # os.system('python ./matching/shixun/youtube_usercf_recall.py')
    # print("**"*10+"dssm_recall_trainl"+"**"*10)
    # os.system('python ./matching/shixun/dssm_recall_train.py')

    # print("**"*10+"dssm_usercf_recall"+"**"*10)   
    # os.system('python ./matching/shixun/dssm_usercf_recall.py')
    # print("**"*10+"fm_recall_train"+"**"*10) 
    # os.system('python ./matching/shixun/fm_recall_train.py')
    # print("**"*10+"mind_recall_train"+"**"*10) 
    # os.system('python ./matching/shixun/mind_recall_train.py')
    # print("**"*10+"pinsage_recall_train"+"**"*10) 
    # os.system('python ./matching/shixun/pinsage_recall_train.py')

    # 全量数据计算每路离线召回结果耗时太长
    # 只在增量数据召回时合并多路召回的结果
    # if samples_mode:
    #     print("**"*10+"multi_recall_combine"+"**"*10) 
    #     os.system('python ./matching/shixun/multi_recall_combine.py')

    # 排序特征工程
    # print("**"*10+"bert_embedding"+"**"*10) 
    # os.system('python ./ranking/shixun/bert_embedding.py')
    # print("**"*10+"rank_features_engineering"+"**"*10) 
    # os.system('python ./ranking/shixun/rank_features_engineering.py')
    time.sleep(60*60*4)
    # 训练排序模型
    print("**"*10+"xdeepfm_ranker_train"+"**"*10)
    os.system('python ./ranking/shixun/xdeepfm_ranker_train.py')
    print("**"*10+"difm_ranker_train"+"**"*10)
    os.system('python ./ranking/shixun/difm_ranker_train.py')
    print("**"*10+"bst_ranker_train"+"**"*10)
    os.system('python ./ranking/shixun/bst_ranker_train.py')