diff --git a/paddle/operators/reshape_op.cc b/paddle/operators/reshape_op.cc
index 1b073a79bcaf48663a80c7619af4a334d32cbfc3..d75ec766325ce8ae30918b7efd7171c17b3b8be2 100644
--- a/paddle/operators/reshape_op.cc
+++ b/paddle/operators/reshape_op.cc
@@ -38,6 +38,7 @@ class ReshapeOp : public framework::OperatorWithKernel {
     size_t in_size = framework::product(in->dims());
     PADDLE_ENFORCE_EQ(shape_size, in_size,
                       "The size of Input(X) mismatches with Attr(shape).");
+    ctx.Output<framework::Tensor>("Out")->Resize(in->dims());
   }
 };
 
@@ -51,7 +52,7 @@ class ReshapeOpMaker : public framework::OpProtoAndCheckerMaker {
     AddAttr<std::vector<int>>("shape", "Target shape of reshape operator.");
     AddComment(R"DOC(Reshape operator
 
-The input tensor will be reshaped with Attr(shape).
+Reshape Input(X) into the shape specified by Attr(shape).
 )DOC");
   }
 };
diff --git a/paddle/operators/reshape_op.h b/paddle/operators/reshape_op.h
index 22ede88b12c7704e6637b87fd9cf792851a2302f..61d502c836cb06fc741cca2e1702c0a39fd400df 100644
--- a/paddle/operators/reshape_op.h
+++ b/paddle/operators/reshape_op.h
@@ -23,13 +23,13 @@ namespace operators {
 
 using Tensor = framework::Tensor;
 
-template <typename Place, typename T, typename AttrType = T>
+template <typename Place, typename T>
 class ReshapeKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& ctx) const {
     auto* out = ctx.Output<Tensor>("Out");
     auto* in = ctx.Input<Tensor>("X");
-    out->mutable_data<T>(in->place());
+    out->mutable_data<T>(ctx.GetPlace());
 
     auto shape = ctx.Attr<std::vector<int>>("shape");
     std::vector<int64_t> tmp;
@@ -42,7 +42,7 @@ class ReshapeKernel : public framework::OpKernel {
   }
 };
 
-template <typename Place, typename T, typename AttrType = T>
+template <typename Place, typename T>
 class ReshapeGradKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& ctx) const {
@@ -51,7 +51,6 @@ class ReshapeGradKernel : public framework::OpKernel {
     d_x->mutable_data<T>(ctx.GetPlace());
 
     auto in_dims = d_x->dims();
-
     d_x->CopyFrom<T>(*d_out, ctx.GetPlace());
     d_x->Resize(in_dims);
   }
diff --git a/python/paddle/v2/framework/tests/test_reshape_op.py b/python/paddle/v2/framework/tests/test_reshape_op.py
index c101b0df9ad4ef1ab919d385a08f877736faab76..47970194353f4f64613f97c1deaed1f52c47af3c 100644
--- a/python/paddle/v2/framework/tests/test_reshape_op.py
+++ b/python/paddle/v2/framework/tests/test_reshape_op.py
@@ -1,6 +1,6 @@
 import unittest
 import numpy as np
-from gradient_checker import GradientChecker, create_op
+from gradient_checker import GradientChecker, Operator
 from op_test_util import OpTestMeta
 
 
@@ -9,19 +9,16 @@ class TestReshapeOp(unittest.TestCase):
 
     def setUp(self):
         self.type = "reshape"
-        self.inputs = {'X': np.random.random((2, 4)).astype("float32"), }
-        print self.inputs
-        self.attrs = {'shape': [4, 2]}
+        self.inputs = {'X': np.random.random((37, 51)).astype("float32"), }
+        self.attrs = {'shape': [51, 37]}
         self.outputs = {'Out': self.inputs['X'].reshape(self.attrs['shape'])}
-        print self.outputs
 
 
 class ReshapeGradOpTest(GradientChecker):
     def test_normal(self):
-        op = create_op("reshape")
-        inputs = {"X": np.random.random((2, 4)).astype("float32")}
-        attrs = {'shape': [4, 2]}
-        self.check_grad(op, inputs, attrs, set("X"), "Out")
+        op = Operator("reshape", X='X', Out='Out', shape=[5, 40])
+        inputs = {"X": np.random.random((10, 20)).astype("float32")}
+        self.check_grad(op, inputs, set("X"), "Out")
 
 
 if __name__ == '__main__':