Created by: lerry-lee

保存可服务模型时，顺便打印了输入输出变量的名称

    inference_model_dir = "bow_pairwise/exp1"

    serving_client_dir = "temp/serving_client"
  
    serving_server_dir = "temp/serving_server"
   
    feed_var_names, fetch_var_names = inference_model_to_serving(    
        infer_model=inference_model_dir, serving_client=serving_client_dir,      serving_server=serving_server_dir)

    print("feed_names:",feed_var_names)
 
    print("fetch_names:",fetch_var_names)

打印结果为

feed_names: dict_keys(['read_file_0.tmp_0', 'read_file_0.tmp_1'])  
fetch_names: dict_keys(['fc.tmp_1', 'cos_sim_0.tmp_0'])

于是我按照这个名称来定义输入、获取输出. 启动好rpc预测服务后，调用client测试

    vocab = load_vocab('term2id.dict')    
    str_list = ['你好\t你好\t1']    
    left, pos_right = Sim_reader(str_list, vocab)    
    client = Client()    
    client.load_client_config("temp/serving_server/serving_client_conf.prototxt")    
    client.connect(["127.0.0.1:9292"])    
    feed={'read_file_0.tmp_0':left,'read_file_0.tmp_1':pos_right}    
    fetch=['fc.tmp_1','cos_sim_0.tmp_0']    
    fetch_res = client.predict(feed=feed, fetch=fetch) 

其中Sim_reader是模仿源码里面的数据读取方式写的

def Sim_reader(str_list, vocab):    
    simnet_process = SimNetProcessor(str_list, vocab)    
    startup_prog = fluid.Program()    
    get_test_examples = simnet_process.get_reader()    
    batch_data = fluid.io.batch(    
        get_test_examples, 128, drop_last=False)    
    test_prog = fluid.Program()    
    inf_pyreader = fluid.layers.py_reader(    
        capacity=16,    
        shapes=([-1], [-1]),  
        dtypes=('int64', 'int64'),  
        lod_levels=(1, 1),  
        name='test_reader',  
        use_double_buffer=False)  
    inf_pyreader.decorate_paddle_reader(batch_data)  
    left, right = fluid.layers.read_file(inf_pyreader)  
    return left, right

其中SimNetProcessor源码里是从文件中一行一行读，我改写成从list中按元素读了. 然后我执行客户端测试，发现报一些错误

fetch_map = client.predict(feed=feed, fetch=fetch)
  File "/home/lca/.conda/envs/py36-paddle/lib/python3.6/site-packages/paddle_serving_client/__init__.py", line 296, in predict
    int_feed_names, int_shape, fetch_names, result_batch, self.pid)
ValueError: vector::reserve

我尝试打印过left,pos_right，是variable的类型，里面还有lod_tensor，不知道是不是里面没有实际数据...