diff --git a/python/paddle_serving_client/__init__.py b/python/paddle_serving_client/__init__.py
index b3687b7b5caef240035127fc0bfbce394acb8260..979a2f9e981cc287bbc877268a2c001c54f05f95 100644
--- a/python/paddle_serving_client/__init__.py
+++ b/python/paddle_serving_client/__init__.py
@@ -410,7 +410,11 @@ class GClient(object):
             if self.feed_types_[var.alias_name] == 'float':
                 self.feed_types_[var.alias_name] = 'float32'
             if var.is_lod_tensor:
-                self.lod_tensor_set_.add(var.alias_name)
+                self.lod_tensor_set.add(var.alias_name)
+            else:
+                counter = 1
+                for dim in self.feed_shapes_[var.alias_name]:
+                    counter *= dim
         for i, var in enumerate(model_conf.fetch_var):
             self.fetch_types_[var.alias_name] = var.fetch_type
             if self.fetch_types_[var.alias_name] == 'float':
@@ -435,6 +439,14 @@ class GClient(object):
                 itype = self.type_map_[self.feed_types_[name]]
                 data = np.array(var, dtype=itype)
                 inst.data.append(data.tobytes())
+                if isinstance(var, np.ndarray):
+                    inst.shape.append(
+                        np.array(
+                            list(var.shape), dtype="int32").tobytes())
+                else:
+                    inst.shape.append(
+                        np.array(
+                            self.feed_shapes_[name], dtype="int32").tobytes())
             req.feed_insts.append(inst)
         return req
 
diff --git a/python/paddle_serving_server/__init__.py b/python/paddle_serving_server/__init__.py
index c5c4734b3c2257aef556e7cb9fcc941f4bc9349b..56ddaf96742e6fe51a7d697bb8a5c993fbd029bb 100644
--- a/python/paddle_serving_server/__init__.py
+++ b/python/paddle_serving_server/__init__.py
@@ -481,8 +481,10 @@ class GServerService(
             feed_dict = {}
             for idx, name in enumerate(feed_inst.names):
                 data = feed_inst.data[idx]
+                shape = feed_inst.shape[idx]
                 itype = self.type_map_[self.feed_types_[name]]
                 feed_dict[name] = np.frombuffer(data, dtype=itype)
+                feed_dict[name].shape = np.frombuffer(shape, dtype="int32")
             feed_batch.append(feed_dict)
         return feed_batch, fetch_names