diff --git a/python/paddle_serving_client/__init__.py b/python/paddle_serving_client/__init__.py
index 39e06ef14d9f2ab64bee0730ef29b03a5e2dc923..e0adc6e3cbe629d39a0293ba0e362d5115cf4d21 100644
--- a/python/paddle_serving_client/__init__.py
+++ b/python/paddle_serving_client/__init__.py
@@ -175,7 +175,6 @@ class Client(object):
         return self.fetch_names_
 
     def shape_check(self, feed, key):
-        seq_shape = 1
         if key in self.lod_tensor_set:
             return
         if len(feed[key]) != self.feed_tensor_len[key]:
@@ -192,7 +191,7 @@ class Client(object):
         elif isinstance(fetch, list):
             fetch_list = fetch
         else:
-            raise ValueError("fetch only accepts string and list of string")
+            raise ValueError("Fetch only accepts string and list of string")
 
         feed_batch = []
         if isinstance(feed, dict):
@@ -200,7 +199,7 @@ class Client(object):
         elif isinstance(feed, list):
             feed_batch = feed
         else:
-            raise ValueError("feed only accepts dict and list of dict")
+            raise ValueError("Feed only accepts dict and list of dict")
 
         int_slot_batch = []
         float_slot_batch = []
@@ -216,7 +215,7 @@ class Client(object):
 
         if len(fetch_names) == 0:
             raise ValueError(
-                "fetch names should not be empty or out of saved fetch list")
+                "Fetch names should not be empty or out of saved fetch list.")
             return {}
 
         for i, feed_i in enumerate(feed_batch):
@@ -224,7 +223,8 @@ class Client(object):
             float_slot = []
             for key in feed_i:
                 if key not in self.feed_names_:
-                    continue
+                    raise ValueError("Wrong feed name: {}.".format(key))
+                self.shape_check(feed_i, key)
                 if self.feed_types_[key] == int_type:
                     if i == 0:
                         int_feed_names.append(key)
@@ -233,6 +233,8 @@ class Client(object):
                     if i == 0:
                         float_feed_names.append(key)
                     float_slot.append(feed_i[key])
+            if len(int_slot) + len(float_slot) == 0:
+                raise ValueError("No feed data for predict.")
             int_slot_batch.append(int_slot)
             float_slot_batch.append(float_slot)