fix bug

core/general-client/include/general_model.h

@@ -49,6 +49,8 @@ class ModelRes {
                             res._int64_value_map.end());
     _float_value_map.insert(res._float_value_map.begin(),
                             res._float_value_map.end());
+    _shape_map.insert(res._shape_map.begin(), res._shape_map.end());
+    _lod_map.insert(res._lod_map.begin(), res._lod_map.end());
   }
   ModelRes(ModelRes&& res) {
     _engine_name = std::move(res._engine_name);
@@ -58,6 +60,10 @@ class ModelRes {
     _float_value_map.insert(
         std::make_move_iterator(std::begin(res._float_value_map)),
         std::make_move_iterator(std::end(res._float_value_map)));
+    _shape_map.insert(std::make_move_iterator(std::begin(res._shape_map)),
+                      std::make_move_iterator(std::end(res._shape_map)));
+    _lod_map.insert(std::make_move_iterator(std::begin(res._lod_map)),
+                    std::make_move_iterator(std::end(res._lod_map)));
   }
   ~ModelRes() {}
   const std::vector<int64_t>& get_int64_by_name(const std::string& name) {
@@ -85,6 +91,10 @@ class ModelRes {
       _float_value_map.insert(
           std::make_move_iterator(std::begin(res._float_value_map)),
           std::make_move_iterator(std::end(res._float_value_map)));
+      _shape_map.insert(std::make_move_iterator(std::begin(res._shape_map)),
+                        std::make_move_iterator(std::end(res._shape_map)));
+      _lod_map.insert(std::make_move_iterator(std::begin(res._lod_map)),
+                      std::make_move_iterator(std::end(res._lod_map)));
     }
     return *this;
   }

doc/MODEL_ENSEMBLE_IN_PADDLE_SERVING.md

@@ -100,11 +100,11 @@ for i in range(3):
     fetch = ["acc", "cost", "prediction"]
     fetch_maps = client.predict(feed=feed, fetch=fetch)
     if len(fetch_maps) == 1:
-        print("step: {}, res: {}".format(i, fetch_maps['prediction'][1]))
+        print("step: {}, res: {}".format(i, fetch_maps['prediction'][0][1]))
     else:
         for model, fetch_map in fetch_maps.items():
             print("step: {}, model: {}, res: {}".format(i, model, fetch_map[
-                'prediction'][1]))
+                'prediction'][0][1]))
 ```
 
 Compared with the normal prediction service, the client side has not changed much. When multiple model predictions are used, the prediction service will return a dictionary with engine name `engine_name`(the value is defined on the server side) as the key, and the corresponding model prediction results as the value.

doc/MODEL_ENSEMBLE_IN_PADDLE_SERVING_CN.md

@@ -100,11 +100,11 @@ for i in range(3):
     fetch = ["acc", "cost", "prediction"]
     fetch_maps = client.predict(feed=feed, fetch=fetch)
     if len(fetch_maps) == 1:
-        print("step: {}, res: {}".format(i, fetch_maps['prediction'][1]))
+        print("step: {}, res: {}".format(i, fetch_maps['prediction'][0][1]))
     else:
         for model, fetch_map in fetch_maps.items():
             print("step: {}, model: {}, res: {}".format(i, model, fetch_map[
-                'prediction'][1]))
+                'prediction'][0][1]))
 ```
 
 Client端与普通预测服务没有发生太大的变化。当使用多个模型预测时，预测服务将返回一个key为Server端定义的引擎名称`engine_name`，value为对应的模型预测结果的字典。

python/examples/imdb/test_ensemble_client.py

@@ -35,8 +35,8 @@ for i in range(3):
     fetch = ["acc", "cost", "prediction"]
     fetch_maps = client.predict(feed=feed, fetch=fetch)
     if len(fetch_maps) == 1:
-        print("step: {}, res: {}".format(i, fetch_maps['prediction'][1]))
+        print("step: {}, res: {}".format(i, fetch_maps['prediction'][0][1]))
     else:
         for model, fetch_map in fetch_maps.items():
             print("step: {}, model: {}, res: {}".format(i, model, fetch_map[
-                'prediction'][1]))
+                'prediction'][0][1]))