diff --git a/paddle/cuda/src/hl_cuda_cnn.cu b/paddle/cuda/src/hl_cuda_cnn.cu
index a91ead240416e8aba3259fa785f6dfda596be44e..3699b1e8ae9d8f813439eaeaa760c4a9f6e100a0 100644
--- a/paddle/cuda/src/hl_cuda_cnn.cu
+++ b/paddle/cuda/src/hl_cuda_cnn.cu
@@ -51,8 +51,8 @@ __global__ void KeMaxPoolForward(const int nthreads,
     for (int h = hstart; h < hend; ++h) {
       for (int w = wstart; w < wend; ++w) {
         if (maxval < inputData[h * width + w]) {
-          maxval = inputData[h * width + w];
           max_index = h * width + w;
+          maxval = inputData[max_index];
         }
       }
     }
diff --git a/paddle/gserver/tests/test_MaxPoolingWithMaskOutput.cpp b/paddle/gserver/tests/test_MaxPoolingWithMaskOutput.cpp
index 44fc2b91ec334ff1618328e44a5e8bd44d82c4b9..16438886df94cab9d29d05924bb047e6c7f1f6fa 100644
--- a/paddle/gserver/tests/test_MaxPoolingWithMaskOutput.cpp
+++ b/paddle/gserver/tests/test_MaxPoolingWithMaskOutput.cpp
@@ -105,15 +105,13 @@ TEST(Layer, maxPoolingWithMaskOutputLayerFwd) {
   maskMat->setData(maskData);
   doOneMaxPoolingWithMaskOutputTest(
       inputMat, "max-pool-with-mask", useGpu, maskMat);
-  /*
-  #ifdef PADDLE_WITH_CUDA
-    useGpu = true;
-    inputMat = Matrix::create(1, 25, false, useGpu);
-    maskMat = Matrix::create(1, 4, false, useGpu);
-    inputMat->copyFrom(inputData, 25);
-    maskMat->copyFrom(maskData, 4);
-    doOneMaxPoolingWithMaskOutputTest(
-        inputMat, "max-pool-with-mask", useGpu, maskMat);
-  #endif
-  */
+#ifdef PADDLE_WITH_CUDA
+  useGpu = true;
+  inputMat = Matrix::create(1, 25, false, useGpu);
+  maskMat = Matrix::create(1, 4, false, useGpu);
+  inputMat->copyFrom(inputData, 25);
+  maskMat->copyFrom(maskData, 4);
+  doOneMaxPoolingWithMaskOutputTest(
+      inputMat, "max-pool-with-mask", useGpu, maskMat);
+#endif
 }
diff --git a/paddle/math/Matrix.cpp b/paddle/math/Matrix.cpp
index 743922cd9bd65b311cf47659be83f55712b8d5ac..41ee5089677f2565dfd16b1bca7885db5583d910 100644
--- a/paddle/math/Matrix.cpp
+++ b/paddle/math/Matrix.cpp
@@ -2021,7 +2021,7 @@ void CpuMatrix::maxPoolForward(Matrix& inputMat,
           int wstart = pw * strideW - paddingW;
           int wend = std::min(wstart + sizeX, imgSizeW);
           wstart = std::max(wstart, 0);
-          if (maskMatP == NULL) {
+          if (maskData == NULL) {
             for (int h = hstart; h < hend; ++h) {
               for (int w = wstart; w < wend; ++w) {
                 outData[ph * outputW + pw] = std::max(
@@ -2044,7 +2044,7 @@ void CpuMatrix::maxPoolForward(Matrix& inputMat,
       inputData += inLength;
       outData += outLength;
 
-      if (maskMatP != NULL) maskData += outLength;
+      if (maskData != NULL) maskData += outLength;
     }
   }
 }
diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py
index f7ab7a5ca0a369e976c783fdc793abd69a683c3c..e21071f5b020156713f31aa4fc7266aed5cd9cfa 100644
--- a/python/paddle/trainer_config_helpers/layers.py
+++ b/python/paddle/trainer_config_helpers/layers.py
@@ -2701,7 +2701,7 @@ def img_pool_layer(input,
 
     assert type(pool_type) in [AvgPooling, MaxPooling, MaxWithMaskPooling, CudnnAvgPooling,
                                CudnnMaxPooling], \
-        "only (Cudnn)AvgPooling, (Cudnn)MaxPooling MaxWithMaskPooling are supported"
+        "only (Cudnn)AvgPooling, (Cudnn)MaxPooling, MaxWithMaskPooling are supported"
 
     type_name = pool_type.name + '-projection' \
         if (