diff --git a/core/configure/proto/general_model_config.proto b/core/configure/proto/general_model_config.proto
index 310ad9e2eb612687d360edba82afa3aaf2c71885..22f31047f11f8642ce53261fc2ac720448918485 100644
--- a/core/configure/proto/general_model_config.proto
+++ b/core/configure/proto/general_model_config.proto
@@ -15,17 +15,15 @@
 syntax = "proto2";
 package baidu.paddle_serving.configure;
 
-message Shape { repeated int32 shape = 1; };
-
 message FeedVar {
   required string name = 1;
   required bool is_lod_tensor = 2;
   required int32 feed_type = 3;
-  required Shape feed_shape = 4;
+  repeated int32 shape = 4;
 }
 message FetchVar {
   required string name = 1;
-  required Shape fetch_shape = 2;
+  repeated int32 shape = 2;
 }
 message GeneralModelConfig {
   repeated FeedVar feed_var = 1;
diff --git a/core/predictor/framework/resource.cpp b/core/predictor/framework/resource.cpp
index 0fa5e035b290ab8ff9dcc2d980561ccd014b33c2..e24f3e88b9ad9bce4f625f8e99a34bb815d21f94 100644
--- a/core/predictor/framework/resource.cpp
+++ b/core/predictor/framework/resource.cpp
@@ -23,7 +23,6 @@ namespace predictor {
 
 using configure::ResourceConf;
 using configure::GeneralModelConfig;
-using configure::Shape;
 using rec::mcube::CubeAPI;
 // __thread bool p_thread_initialized = false;
 
@@ -198,9 +197,8 @@ int Resource::general_model_initialize(const std::string& path,
     } else {
       _config->_capacity[i] = 1;
       _config->_is_lod_feed[i] = false;
-      for (int j = 0; j < model_config.feed_var(i).feed_shape().shape_size();
-           ++j) {
-        int32_t dim = model_config.feed_var(i).feed_shape().shape(j);
+      for (int j = 0; j < model_config.feed_var(i).shape_size(); ++j) {
+        int32_t dim = model_config.feed_var(i).shape(j);
         _config->_feed_shape[i].push_back(dim);
         _config->_capacity[i] *= dim;
       }
@@ -212,9 +210,8 @@ int Resource::general_model_initialize(const std::string& path,
   _config->_fetch_shape.resize(fetch_var_num);
   for (int i = 0; i < fetch_var_num; ++i) {
     _config->_fetch_name[i] = model_config.fetch_var(i).name();
-    for (int j = 0; j < model_config.fetch_var(i).fetch_shape().shape_size();
-         ++j) {
-      int dim = model_config.fetch_var(i).fetch_shape().shape(j);
+    for (int j = 0; j < model_config.fetch_var(i).shape_size(); ++j) {
+      int dim = model_config.fetch_var(i).shape(j);
       _config->_fetch_shape[i].push_back(dim);
     }
   }
diff --git a/examples/demo-serving/conf/general_model.prototxt b/examples/demo-serving/conf/general_model.prototxt
index efb0913731a309fbc6d9214091303a18bf485a24..984526e6c8152c35639a9a04e15ee3fd22dd16b5 100644
--- a/examples/demo-serving/conf/general_model.prototxt
+++ b/examples/demo-serving/conf/general_model.prototxt
@@ -1,34 +1,24 @@
 feed_var {
     name: "words"
-    is_lod_tensor: false
+    is_lod_tensor: true
     feed_type: 0
-    feed_shape {
-        shape: -1
-    }
+    shape: -1
 }
 feed_var {
     name: "label"
     is_lod_tensor: false
     feed_type: 0
-    feed_shape {
-        shape: 1    
-    }
+    shape: 1    
 }
 fetch_var {
-    name: "mean_0.tmp_0"
-    fetch_shape {
-        shape: 1
-    }
+    name: "cost"
+    shape: 1
 }
 fetch_var {
-    name: "accuracy_0.tmp_0"
-    fetch_shape {
-        shape: 1
-    }
+    name: "acc"
+    shape: 1
 }
 fetch_var {
-    name: "fc_1.tmp_2"
-    fetch_shape {
-        shape: 1
-    }
+    name: "prediction"
+    shape: 2
 }
diff --git a/examples/demo-serving/op/general_model_op.cpp b/examples/demo-serving/op/general_model_op.cpp
index 1b6c3695949894acd17c7c9a1ef717710a23f14b..3e4896b3613d0914fc638fcf1d016460d5aaa056 100644
--- a/examples/demo-serving/op/general_model_op.cpp
+++ b/examples/demo-serving/op/general_model_op.cpp
@@ -48,16 +48,6 @@ int GeneralModelOp::inference() {
   std::vector<int> elem_size;
   std::vector<int> capacity;
 
-  // config
-  LOG(INFO) << "start to call load general model_conf op";
-  baidu::paddle_serving::predictor::Resource &resource =
-      baidu::paddle_serving::predictor::Resource::instance();
-  LOG(INFO) << "get resource pointer done.";
-  std::shared_ptr<PaddleGeneralModelConfig> model_config =
-      resource.get_general_model_config();
-  LOG(INFO) << "get general model config pointer done.";
-  resource.print_general_model_config(model_config);
-
   // infer
   if (batch_size > 0) {
     int var_num = req->insts(0).tensor_array_size();