diff --git a/python/paddle/v2/fluid/backward.py b/python/paddle/v2/fluid/backward.py
index b90949838ea5ccaae3111164214f15a8b5579e87..6966cc75804b6b5a49ceb45a26994c23d2936bdb 100644
--- a/python/paddle/v2/fluid/backward.py
+++ b/python/paddle/v2/fluid/backward.py
@@ -195,7 +195,7 @@ def _append_backward_vars_(block, start_op_idx, grad_to_var, grad_info_map):
                 _infer_var_data_type_(arg, block)
 
 
-def append_backward(loss, parameter_list=None, no_grad_dict=None):
+def append_backward(loss, parameter_list=None, no_grad_set=None):
     """
     Create and add gradient Operators in BlockDesc to compute
     gradients of `loss` for parameters in parameter_list
@@ -213,8 +213,8 @@ def append_backward(loss, parameter_list=None, no_grad_dict=None):
     assert isinstance(loss, framework.Variable)
 
     program = loss.block.program
-    if no_grad_dict is None:
-        no_grad_dict = dict()
+    no_grad_dict = dict()
+    if no_grad_set is None:
         assert isinstance(program, framework.Program)
         for block in program.blocks:
             assert isinstance(block, framework.Block)
@@ -224,8 +224,10 @@ def append_backward(loss, parameter_list=None, no_grad_dict=None):
                 if var.stop_gradient:
                     block_no_grad_set.add(_append_grad_suffix_(var.name))
             no_grad_dict[block.idx] = block_no_grad_set
-    elif isinstance(no_grad_dict, set):
-        no_grad_dict = {0: no_grad_dict}
+    elif isinstance(no_grad_set, set):
+        no_grad_dict = {0: no_grad_set}
+    else:
+        raise ValueError("'no_grad_set' should be a set or None.")
 
     grad_info_map = dict()
     root_block = program.block(0)