diff --git a/paddle/operators/math/pool_test_maxPool2d.cc b/paddle/operators/math/pool_test_maxPool2d.cc
index 8ddf1d79c7a9213064dd4049fd2ded68dece983e..63b6b5657bea457d3d5aa2a4727842d8f9632401 100644
--- a/paddle/operators/math/pool_test_maxPool2d.cc
+++ b/paddle/operators/math/pool_test_maxPool2d.cc
@@ -23,16 +23,17 @@
 
 #ifndef PADDLE_ONLY_CPU
 
-template <typename PooType>
-void testPool2d(paddle::platform::DeviceContext& context, PooType pool_process,
-                paddle::framework::Tensor& input,
+template <typename PoolType, typename PoolGradType>
+void testPool2d(paddle::platform::DeviceContext& context, PoolType pool_process,
+                PoolGradType poolGrad_process, paddle::framework::Tensor& input,
                 paddle::framework::Tensor& input_grad,
                 paddle::framework::Tensor& output,
                 paddle::framework::Tensor& output_grad, std::vector<int>& ksize,
                 std::vector<int>& strides, std::vector<int>& paddings) {
   paddle::operators::math::Pool2dForwardFunctor<paddle::platform::GPUPlace,
-                                                PooType, float>
+                                                PoolType, float>
       pool2d_forward;
+
   pool2d_forward(context, input, output, ksize, strides, paddings,
                  pool_process);
 
@@ -44,10 +45,11 @@ void testPool2d(paddle::platform::DeviceContext& context, PooType pool_process,
   start = clock();
   for (int i = 0; i < times; ++i) {
     paddle::operators::math::Pool2dBackwardFunctor<paddle::platform::GPUPlace,
-                                                   PooType, float>
+                                                   PoolGradType, float>
         pool2d_backward;
     pool2d_backward(context, input, input_grad, output, output_grad, ksize,
-                    strides, paddings, pool_process);
+                    strides, paddings, poolGrad_process);
+
     PADDLE_ENFORCE(cudaStreamSynchronize(0),
                    "cudaStreamSynchronize failed in pool2d_backward CopyFrom");
   }
@@ -136,10 +138,12 @@ void test2dPool() {
   paddle::platform::DeviceContext* context =
       new paddle::platform::CUDADeviceContext(paddle::platform::GPUPlace());
   paddle::operators::math::pool::maxPool<float> pool_process;
+  paddle::operators::math::pool::maxPoolGrad<float> poolGrad_process;
 
-  testPool2d<paddle::operators::math::pool::maxPool<float>>(
-      *context, pool_process, input, input_grad, output, output_grad, ksize,
-      strides, paddings);
+  testPool2d<paddle::operators::math::pool::maxPool<float>,
+             paddle::operators::math::pool::maxPoolGrad<float>>(
+      *context, pool_process, poolGrad_process, input, input_grad, output,
+      output_grad, ksize, strides, paddings);
 }
 
 int main() {
diff --git a/paddle/operators/math/pool_test_maxPool3d.cc b/paddle/operators/math/pool_test_maxPool3d.cc
index 000b006a1281d99d3427740bc7b0f9ed3da5d1dd..ce572164c4f800c712e04fd2bb359ac793c042dd 100644
--- a/paddle/operators/math/pool_test_maxPool3d.cc
+++ b/paddle/operators/math/pool_test_maxPool3d.cc
@@ -23,15 +23,15 @@
 
 #ifndef PADDLE_ONLY_CPU
 
-template <typename PooType>
-void testPool3d(paddle::platform::DeviceContext& context, PooType pool_process,
-                paddle::framework::Tensor& input,
+template <typename PoolType, typename PoolGradType>
+void testPool3d(paddle::platform::DeviceContext& context, PoolType pool_process,
+                PoolGradType poolGrad_process, paddle::framework::Tensor& input,
                 paddle::framework::Tensor& input_grad,
                 paddle::framework::Tensor& output,
                 paddle::framework::Tensor& output_grad, std::vector<int>& ksize,
                 std::vector<int>& strides, std::vector<int>& paddings) {
   paddle::operators::math::Pool3dForwardFunctor<paddle::platform::GPUPlace,
-                                                PooType, float>
+                                                PoolType, float>
       pool3d_forward;
   pool3d_forward(context, input, output, ksize, strides, paddings,
                  pool_process);
@@ -44,10 +44,10 @@ void testPool3d(paddle::platform::DeviceContext& context, PooType pool_process,
   start = clock();
   for (int i = 0; i < times; ++i) {
     paddle::operators::math::Pool3dBackwardFunctor<paddle::platform::GPUPlace,
-                                                   PooType, float>
+                                                   PoolGradType, float>
         pool3d_backward;
     pool3d_backward(context, input, input_grad, output, output_grad, ksize,
-                    strides, paddings, pool_process);
+                    strides, paddings, poolGrad_process);
     PADDLE_ENFORCE(cudaStreamSynchronize(0),
                    "cudaStreamSynchronize failed in pool3d_backward CopyFrom");
   }
@@ -145,9 +145,12 @@ void test3dPool() {
       new paddle::platform::CUDADeviceContext(paddle::platform::GPUPlace());
   paddle::operators::math::pool::maxPool<float> pool_process;
 
-  testPool3d<paddle::operators::math::pool::maxPool<float>>(
-      *context, pool_process, input, input_grad, output, output_grad, ksize,
-      strides, paddings);
+  paddle::operators::math::pool::maxPoolGrad<float> poolGrad_process;
+
+  testPool3d<paddle::operators::math::pool::maxPool<float>,
+             paddle::operators::math::pool::maxPoolGrad<float>>(
+      *context, pool_process, poolGrad_process, input, input_grad, output,
+      output_grad, ksize, strides, paddings);
 }
 
 int main() { test3dPool(); }
diff --git a/paddle/operators/math/pooling.cc b/paddle/operators/math/pooling.cc
index 6539b80678431d3edf5d9cdf8da5a1e27a3b85e0..cb1f9d72857592bd8cb6d4532170d03a11e45343 100644
--- a/paddle/operators/math/pooling.cc
+++ b/paddle/operators/math/pooling.cc
@@ -196,7 +196,7 @@ class MaxPool2dBackwardFunctor<platform::CPUPlace, T> {
 };
 
 template class MaxPool2dBackwardFunctor<platform::CPUPlace, float>;
-template class MaxPool2dBackwardFunctor<platform::CPUPlace, double>;
+// template class MaxPool2dBackwardFunctor<platform::CPUPlace, double>;
 
 template class Pool2dForwardFunctor<
     platform::CPUPlace, paddle::operators::math::pool::maxPool<float>, float>;
@@ -443,7 +443,7 @@ class MaxPool3dBackwardFunctor<platform::CPUPlace, T> {
 };
 
 template class MaxPool3dBackwardFunctor<platform::CPUPlace, float>;
-template class MaxPool3dBackwardFunctor<platform::CPUPlace, double>;
+// template class MaxPool3dBackwardFunctor<platform::CPUPlace, double>;
 
 template class Pool3dForwardFunctor<
     platform::CPUPlace, paddle::operators::math::pool::maxPool<float>, float>;
diff --git a/paddle/operators/pool_op.h b/paddle/operators/pool_op.h
index 6f1d05272cd1e66f8858d19454fe7dc08ce7b45d..763103d884bb223a0ec6767299a22ca3259c0cc8 100644
--- a/paddle/operators/pool_op.h
+++ b/paddle/operators/pool_op.h
@@ -111,12 +111,10 @@ class PoolGradKernel : public framework::OpKernel {
       switch (ksize.size()) {
         case 2: {
           if (pooling_type == "max") {
-            paddle::operators::math::Pool2dBackwardFunctor<
-                Place, paddle::operators::math::pool::maxPoolGrad<T>, T>
+            paddle::operators::math::MaxPool2dBackwardFunctor<Place, T>
                 pool2d_backward;
-            paddle::operators::math::pool::maxPoolGrad<T> pool_process;
             pool2d_backward(context.device_context(), *in_X, *in_X_grad, *out,
-                            *out_grad, ksize, strides, paddings, pool_process);
+                            *out_grad, ksize, strides, paddings);
           } else if (pooling_type == "avg") {
             paddle::operators::math::Pool2dBackwardFunctor<
                 Place, paddle::operators::math::pool::avgPoolGrad<T>, T>
@@ -128,12 +126,10 @@ class PoolGradKernel : public framework::OpKernel {
         } break;
         case 3: {
           if (pooling_type == "max") {
-            paddle::operators::math::Pool3dBackwardFunctor<
-                Place, paddle::operators::math::pool::maxPoolGrad<T>, T>
+            paddle::operators::math::MaxPool3dBackwardFunctor<Place, T>
                 pool3d_backward;
-            paddle::operators::math::pool::maxPoolGrad<T> pool_process;
             pool3d_backward(context.device_context(), *in_X, *in_X_grad, *out,
-                            *out_grad, ksize, strides, paddings, pool_process);
+                            *out_grad, ksize, strides, paddings);
           } else if (pooling_type == "avg") {
             paddle::operators::math::Pool3dBackwardFunctor<
                 Place, paddle::operators::math::pool::avgPoolGrad<T>, T>