diff --git a/python/paddle/v2/framework/tests/gradient_checker.py b/python/paddle/v2/framework/tests/gradient_checker.py
index 8eb9f3f07321d388e0035825b71534b7d9076cf6..ac37671c77b94a45e3589efc13ead8eb17fcb38f 100644
--- a/python/paddle/v2/framework/tests/gradient_checker.py
+++ b/python/paddle/v2/framework/tests/gradient_checker.py
@@ -32,7 +32,8 @@ def get_numeric_gradient(op,
                          output_name,
                          input_to_check,
                          delta=0.005,
-                         local_scope=None):
+                         local_scope=None,
+                         in_place=False):
     """
     Get Numeric Gradient for an operator's input.
     
@@ -90,9 +91,10 @@ def get_numeric_gradient(op,
     # we only compute gradient of one element each time.
     # we use a for loop to compute the gradient of every element.
     for i in xrange(tensor_size):
-        for var_name in input_values:
-            tensor_ = local_scope.find_var(var_name).get_tensor()
-            tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace())
+        if in_place:
+            for var_name in input_values:
+                tensor_ = local_scope.find_var(var_name).get_tensor()
+                tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace())
         # get one input element throw it's index i.
         origin = tensor_to_check.get_float_element(i)
 
@@ -102,9 +104,10 @@ def get_numeric_gradient(op,
         y_pos = get_output()
 
         # plus delta to this element, run op and get the sum of the result tensor.
-        for var_name in input_values:
-            tensor_ = local_scope.find_var(var_name).get_tensor()
-            tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace())
+        if in_place:
+            for var_name in input_values:
+                tensor_ = local_scope.find_var(var_name).get_tensor()
+                tensor_.set(numpy.copy(input_values[var_name]), core.CPUPlace())
         x_neg = origin - delta
         tensor_to_check.set_float_element(i, x_neg)
         y_neg = get_output()
@@ -257,6 +260,7 @@ class GradientChecker(unittest.TestCase):
                    output_name,
                    no_grad_set=None,
                    only_cpu=False,
+                   in_place=False,
                    max_relative_error=0.005):
         """
         :param forward_op: used to create backward_op
@@ -289,7 +293,8 @@ class GradientChecker(unittest.TestCase):
 
         # get numerical gradients
         numeric_grads = [
-            get_numeric_gradient(forward_op, input_vars, output_name, name)
+            get_numeric_gradient(
+                forward_op, input_vars, output_name, name, in_place=in_place)
             for name in inputs_to_check
         ]
 
diff --git a/python/paddle/v2/framework/tests/test_scatter_op.py b/python/paddle/v2/framework/tests/test_scatter_op.py
index e7696844d5dd9df872a82c92f93e26374faa4817..861fe6cf89e3dd6826bbf680c9dfa6116e3223bf 100644
--- a/python/paddle/v2/framework/tests/test_scatter_op.py
+++ b/python/paddle/v2/framework/tests/test_scatter_op.py
@@ -31,7 +31,8 @@ class TestScatterGradOp(GradientChecker):
         output_np[index_np] += updates_np
         inputs = {'Ref': ref_np, 'Index': index_np, 'Updates': updates_np}
         # check gradient
-        self.check_grad(op, inputs, set(["Updates", "Ref"]), "Out")
+        self.check_grad(
+            op, inputs, set(["Updates", "Ref"]), "Out", in_place=True)
 
 
 if __name__ == "__main__":