diff --git a/paddle/function/nnpack/NNPACKConvOp.cpp b/paddle/function/nnpack/NNPACKConvOp.cpp
index f0ec77a5d00333993427fb8d0bc938c884e50c95..00d048eb216baf37c875c870a31cfd55a97f2974 100644
--- a/paddle/function/nnpack/NNPACKConvOp.cpp
+++ b/paddle/function/nnpack/NNPACKConvOp.cpp
@@ -49,9 +49,7 @@ class NNPACKConvFunction : public ConvFunctionBase {
 public:
   void init(const FuncConfig& config) override {
     ConvFunctionBase::init(config);
-    CHECK_EQ(groups_, (size_t)1);
     algorithm_ = get_nnp_convolution_algorithm(config.get<std::string>("algo"));
-    // algorithm_ = nnp_convolution_algorithm_auto;
     transform_strategy_ = nnp_convolution_transform_strategy_compute;
     nnp_status status = nnp_initialize();
     CHECK_EQ(status, nnp_status_success);
@@ -67,8 +65,7 @@ public:
     }
   }
 
-  virtual void check(const BufferArgs& inputs,
-                     const BufferArgs& outputs) override {
+  void check(const BufferArgs& inputs, const BufferArgs& outputs) override {
     const TensorShape& input = inputs[0].shape();
     const TensorShape& filter = inputs[1].shape();
     const TensorShape& output = outputs[0].shape();
@@ -91,8 +88,8 @@ public:
     size_t filterHeight = getFilterHeight(filter);
     size_t filterWidth = getFilterWidth(filter);
     size_t outputChannels = output[1];
-    // size_t outputHeight = output[2];
-    // size_t outputWidth = output[3];
+    size_t outputHeight = output[2];
+    size_t outputWidth = output[3];
 
     nnp_size inputSize = {.width = inputWidth, .height = inputHeight};
     nnp_padding padding = {.top = (size_t)paddingH(),
@@ -171,49 +168,58 @@ public:
       }
     }
 
+    size_t inputOffset = inputChannels / groups_ * inputHeight * inputWidth;
+    size_t outputOffset = outputChannels / groups_ * outputHeight * outputWidth;
+    size_t filterOffset = filter.getElements() / groups_;
+
     if (batchSize == 1) {
-      nnp_status status =
-          nnp_convolution_inference(algorithm_,
-                                    transform_strategy_,
-                                    inputChannels,
-                                    outputChannels,
-                                    inputSize,
-                                    padding,
-                                    kernelSize,
-                                    outputSubsampling,
-                                    inputData,
-                                    filterData,
-                                    nullptr, /* bias */
-                                    outputData,
-                                    bufferPtr,
-                                    sizePtr,
-                                    nnp_activation_identity,
-                                    nullptr,
-                                    threadpool_, /* threadpool */
-                                    nullptr);
-      CHECK_EQ(status, nnp_status_success);
+      for (size_t g = 0; g < groups_; g++) {
+        nnp_status status =
+            nnp_convolution_inference(algorithm_,
+                                      transform_strategy_,
+                                      inputChannels / groups_,
+                                      outputChannels / groups_,
+                                      inputSize,
+                                      padding,
+                                      kernelSize,
+                                      outputSubsampling,
+                                      inputData + inputOffset * g,
+                                      filterData + filterOffset * g,
+                                      nullptr, /* bias */
+                                      outputData + outputOffset * g,
+                                      bufferPtr,
+                                      sizePtr,
+                                      nnp_activation_identity,
+                                      nullptr,
+                                      threadpool_, /* threadpool */
+                                      nullptr);
+        CHECK_EQ(status, nnp_status_success);
+      }
     } else {
-      // only supports stride = 1
-      CHECK_EQ(strideH(), 1);
-      CHECK_EQ(strideW(), 1);
-      nnp_status status = nnp_convolution_output(algorithm_,
-                                                 batchSize,
-                                                 inputChannels,
-                                                 outputChannels,
-                                                 inputSize,
-                                                 padding,
-                                                 kernelSize,
-                                                 inputData,
-                                                 filterData,
-                                                 nullptr, /* bias */
-                                                 outputData,
-                                                 bufferPtr,
-                                                 sizePtr,
-                                                 nnp_activation_identity,
-                                                 nullptr,
-                                                 threadpool_, /* threadpool */
-                                                 nullptr);
-      CHECK_EQ(status, nnp_status_success);
+      for (size_t g = 0; g < groups_; g++) {
+        // only supports stride = 1
+        CHECK_EQ(strideH(), 1);
+        CHECK_EQ(strideW(), 1);
+        nnp_status status =
+            nnp_convolution_output(algorithm_,
+                                   batchSize,
+                                   inputChannels / groups_,
+                                   outputChannels / groups_,
+                                   inputSize,
+                                   padding,
+                                   kernelSize,
+                                   inputData + inputOffset * g,
+                                   filterData + filterOffset * g,
+                                   nullptr, /* bias */
+                                   outputData + outputOffset * g,
+                                   bufferPtr,
+                                   sizePtr,
+                                   nnp_activation_identity,
+                                   nullptr,
+                                   threadpool_, /* threadpool */
+                                   nullptr);
+        CHECK_EQ(status, nnp_status_success);
+      }
     }
   }
 
diff --git a/paddle/gserver/layers/ExpandConvLayer.cpp b/paddle/gserver/layers/ExpandConvLayer.cpp
index 783e02e47cb91e28eb88b079f1e94439d34fa775..0ece2799318ea5ecc91f97f71289d4d07246dcaa 100644
--- a/paddle/gserver/layers/ExpandConvLayer.cpp
+++ b/paddle/gserver/layers/ExpandConvLayer.cpp
@@ -57,8 +57,7 @@ bool ExpandConvLayer::init(const LayerMap &layerMap,
       convGradFilterType = "GemmConvGradFilter";
     }
 
-    if (FLAGS_use_nnpack) {
-      CHECK_EQ(isDeconv_, false);
+    if (FLAGS_use_nnpack && !isDeconv_) {
       createFunction(forward_,
                      "NNPACKConv",
                      FuncConfig()