Merge pull request #1000 from smilejames/develop

FusionConvXXXParam inheritance ConvParam

src/operators/op_param.h

@@ -343,20 +343,22 @@ class OpParam {
 
 #ifdef CONV_OP
 template <typename Dtype>
-class ConvParam : OpParam {
+class ConvParam : public OpParam {
   typedef typename DtypeTensorTrait<Dtype>::gtype GType;
   typedef typename DtypeTensorTrait<Dtype>::rtype RType;
 
  public:
   ConvParam(const VariableNameMap &inputs, const VariableNameMap &outputs,
             const AttributeMap &attrs, const Scope &scope) {
-    filter_ = FilterFrom<GType>(inputs, scope);
-    input_ = InputFrom<GType>(inputs, scope);
-    output_ = OutputFrom<GType>(outputs, scope);
-    strides_ = GetAttr<vector<int>>("strides", attrs);
-    paddings_ = GetAttr<vector<int>>("paddings", attrs);
-    dilations_ = GetAttr<vector<int>>("dilations", attrs);
-    groups = GetAttr<int>("groups", attrs);
+    filter_ = OpParam::FilterFrom<GType>(inputs, scope);
+    input_ = OpParam::InputFrom<GType>(inputs, scope);
+    if (outputs.count("Output")) {
+      output_ = OpParam::OutputFrom<GType>(outputs, scope);
+    }
+    strides_ = OpParam::GetAttr<vector<int>>("strides", attrs);
+    paddings_ = OpParam::GetAttr<vector<int>>("paddings", attrs);
+    dilations_ = OpParam::GetAttr<vector<int>>("dilations", attrs);
+    groups = OpParam::GetAttr<int>("groups", attrs);
   }
 
   const RType *Input() const { return input_; }
@@ -1294,52 +1296,29 @@ using FusionFcReluParam = FusionFcParam<DeviceType>;
 #endif
 
 template <typename Dtype>
-class FusionConvAddParam : public OpParam {
+class FusionConvAddParam : public ConvParam<Dtype> {
   typedef typename DtypeTensorTrait<Dtype>::gtype GType;
   typedef typename DtypeTensorTrait<Dtype>::rtype RType;
 
  public:
   FusionConvAddParam(const VariableNameMap &inputs,
                      const VariableNameMap &outputs, const AttributeMap &attrs,
-                     const Scope &scope) {
-    bias_ = InputYFrom<GType>(inputs, scope);
-    axis_ = GetAttr<int>("axis", attrs);
-    filter_ = FilterFrom<GType>(inputs, scope);
-    input_ = InputFrom<GType>(inputs, scope);
-    output_ = OutFrom<GType>(outputs, scope);
-    strides_ = GetAttr<vector<int>>("strides", attrs);
-    paddings_ = GetAttr<vector<int>>("paddings", attrs);
-    dilations_ = GetAttr<vector<int>>("dilations", attrs);
-    groups = GetAttr<int>("groups", attrs);
+                     const Scope &scope)
+      : ConvParam<Dtype>(inputs, outputs, attrs, scope) {
+    bias_ = OpParam::InputYFrom<GType>(inputs, scope);
+    axis_ = OpParam::GetAttr<int>("axis", attrs);
+    output_ = OpParam::OutFrom<GType>(outputs, scope);
   }
   RType *Bias() const { return bias_; }
 
   const int &Axis() const { return axis_; }
 
-  const RType *Input() const { return input_; }
-
-  const RType *Filter() const { return filter_; }
-
   RType *Output() const { return output_; }
 
-  const vector<int> &Strides() const { return strides_; }
-
-  const vector<int> &Paddings() const { return paddings_; }
-
-  const vector<int> &Dilations() const { return dilations_; }
-
-  const int &Groups() const { return groups; }
-
  protected:
   RType *bias_;
   int axis_;
-  RType *input_;
   RType *output_;
-  RType *filter_;
-  vector<int> strides_;
-  vector<int> paddings_;
-  vector<int> dilations_;
-  int groups;
 #ifdef PADDLE_MOBILE_FPGA
 
  private:
@@ -1366,58 +1345,33 @@ class FusionConvAddReluParam : public FusionConvAddParam<DeviceType> {
 #endif
 
 #ifdef FUSION_CONVADDPRELU_OP
-template <typename DeviceType>
-class FusionConvAddPReluParam : public OpParam {
-  typedef typename DtypeTensorTrait<DeviceType>::gtype GType;
-  typedef typename DtypeTensorTrait<DeviceType>::rtype RType;
+template <typename Dtype>
+class FusionConvAddPReluParam : public ConvParam<Dtype> {
+  typedef typename DtypeTensorTrait<Dtype>::gtype GType;
+  typedef typename DtypeTensorTrait<Dtype>::rtype RType;
 
  public:
   FusionConvAddPReluParam(const VariableNameMap &inputs,
                           const VariableNameMap &outputs,
-                          const AttributeMap &attrs, const Scope &scope) {
-    alpha_ = InputAlphaFrom<GType>(inputs, scope);
-    mode_ = GetAttr<std::string>("mode", attrs);
+                          const AttributeMap &attrs, const Scope &scope)
+      : ConvParam<Dtype>(inputs, outputs, attrs, scope) {
+    alpha_ = OpParam::InputAlphaFrom<GType>(inputs, scope);
+    mode_ = OpParam::GetAttr<std::string>("mode", attrs);
     framework::DDim dims = alpha_->dims();
-    bias_ = InputYFrom<GType>(inputs, scope);
-    axis_ = GetAttr<int>("axis", attrs);
-    filter_ = FilterFrom<GType>(inputs, scope);
-    input_ = InputFrom<GType>(inputs, scope);
-    output_ = OutFrom<GType>(outputs, scope);
-    strides_ = GetAttr<vector<int>>("strides", attrs);
-    paddings_ = GetAttr<vector<int>>("paddings", attrs);
-    dilations_ = GetAttr<vector<int>>("dilations", attrs);
-    groups = GetAttr<int>("groups", attrs);
+    bias_ = OpParam::InputYFrom<GType>(inputs, scope);
+    axis_ = OpParam::GetAttr<int>("axis", attrs);
+    output_ = OpParam::OutFrom<GType>(outputs, scope);
   }
   const RType *InputAlpha() const { return alpha_; }
   const std::string &Mode() const { return mode_; }
   RType *Bias() const { return bias_; }
-
   const int &Axis() const { return axis_; }
-
-  const RType *Input() const { return input_; }
-
-  const RType *Filter() const { return filter_; }
-
   RType *Output() const { return output_; }
 
-  const vector<int> &Strides() const { return strides_; }
-
-  const vector<int> &Paddings() const { return paddings_; }
-
-  const vector<int> &Dilations() const { return dilations_; }
-
-  const int &Groups() const { return groups; }
-
  protected:
   RType *bias_;
   int axis_;
-  RType *input_;
   RType *output_;
-  RType *filter_;
-  vector<int> strides_;
-  vector<int> paddings_;
-  vector<int> dilations_;
-  int groups;
   RType *alpha_;
   std::string mode_;
 #ifdef PADDLE_MOBILE_FPGA
@@ -1433,35 +1387,30 @@ class FusionConvAddPReluParam : public OpParam {
 #endif
 
 #ifdef FUSION_CONVADDADDPRELU_OP
-template <typename DeviceType>
-class FusionConvAddAddPReluParam : public OpParam {
-  typedef typename DtypeTensorTrait<DeviceType>::gtype GType;
-  typedef typename DtypeTensorTrait<DeviceType>::rtype RType;
+template <typename Dtype>
+class FusionConvAddAddPReluParam : public ConvParam<Dtype> {
+  typedef typename DtypeTensorTrait<Dtype>::gtype GType;
+  typedef typename DtypeTensorTrait<Dtype>::rtype RType;
 
  public:
   FusionConvAddAddPReluParam(const VariableNameMap &inputs,
                              const VariableNameMap &outputs,
-                             const AttributeMap &attrs, const Scope &scope) {
-    bias1_ = InputYFrom1<GType>(inputs, scope);
-    alpha_ = InputAlphaFrom<GType>(inputs, scope);
-    mode_ = GetAttr<std::string>("mode", attrs);
+                             const AttributeMap &attrs, const Scope &scope)
+      : ConvParam<Dtype>(inputs, outputs, attrs, scope) {
+    bias1_ = OpParam::InputYFrom1<GType>(inputs, scope);
+    alpha_ = OpParam::InputAlphaFrom<GType>(inputs, scope);
+    mode_ = OpParam::GetAttr<std::string>("mode", attrs);
     framework::DDim dims = alpha_->dims();
-    bias_ = InputYFrom<GType>(inputs, scope);
-    axis_ = GetAttr<int>("axis", attrs);
-    filter_ = FilterFrom<GType>(inputs, scope);
-    input_ = InputFrom<GType>(inputs, scope);
-    output_ = OutFrom<GType>(outputs, scope);
-    strides_ = GetAttr<vector<int>>("strides", attrs);
-    paddings_ = GetAttr<vector<int>>("paddings", attrs);
-    dilations_ = GetAttr<vector<int>>("dilations", attrs);
-    groups = GetAttr<int>("groups", attrs);
-    keyOutput_ = getkey("addOut", inputs, 0);
-    keyX1_ = getkey("addX", inputs, 1);
-    keyY1_ = getkey("Y", inputs, 1);
+    bias_ = OpParam::InputYFrom<GType>(inputs, scope);
+    output_ = OpParam::OutFrom<GType>(outputs, scope);
+    axis_ = OpParam::GetAttr<int>("axis", attrs);
+    keyOutput_ = OpParam::getkey("addOut", inputs, 0);
+    keyX1_ = OpParam::getkey("addX", inputs, 1);
+    keyY1_ = OpParam::getkey("Y", inputs, 1);
     if (keyX1_ == keyOutput_) {
-      bias1_ = InputYFrom1<GType>(inputs, scope);
+      bias1_ = OpParam::InputYFrom1<GType>(inputs, scope);
     } else if (keyY1_ == keyOutput_) {
-      bias1_ = InputXFrom1<GType>(inputs, scope);
+      bias1_ = OpParam::InputXFrom1<GType>(inputs, scope);
     }
   }
   const RType *InputAlpha() const { return alpha_; }
@@ -1471,31 +1420,12 @@ class FusionConvAddAddPReluParam : public OpParam {
   RType *Bias() const { return bias_; }
 
   const int &Axis() const { return axis_; }
-
-  const RType *Input() const { return input_; }
-
-  const RType *Filter() const { return filter_; }
-
   RType *Output() const { return output_; }
 
-  const vector<int> &Strides() const { return strides_; }
-
-  const vector<int> &Paddings() const { return paddings_; }
-
-  const vector<int> &Dilations() const { return dilations_; }
-
-  const int &Groups() const { return groups; }
-
  protected:
   RType *bias_;
   int axis_;
-  RType *input_;
   RType *output_;
-  RType *filter_;
-  vector<int> strides_;
-  vector<int> paddings_;
-  vector<int> dilations_;
-  int groups;
   RType *alpha_;
   std::string mode_;
   RType *bias1_;
@@ -1516,49 +1446,32 @@ class FusionConvAddAddPReluParam : public OpParam {
 
 #ifdef FUSION_CONVADDBNRELU_OP
 template <typename Dtype>
-class FusionConvAddBNReluParam : public OpParam {
+class FusionConvAddBNReluParam : public ConvParam<Dtype> {
   typedef typename DtypeTensorTrait<Dtype>::gtype GType;
   typedef typename DtypeTensorTrait<Dtype>::rtype RType;
 
  public:
   FusionConvAddBNReluParam(const VariableNameMap &inputs,
                            const VariableNameMap &outputs,
-                           const AttributeMap &attrs, const Scope &scope) {
-    bias_ = InputYFrom<GType>(inputs, scope);
-    axis_ = GetAttr<int>("axis", attrs);
-    filter_ = FilterFrom<GType>(inputs, scope);
-    input_ = InputFrom<GType>(inputs, scope);
-    output_ = OutFrom<GType>(outputs, scope);
-    strides_ = GetAttr<vector<int>>("strides", attrs);
-    paddings_ = GetAttr<vector<int>>("paddings", attrs);
-    dilations_ = GetAttr<vector<int>>("dilations", attrs);
-    groups = GetAttr<int>("groups", attrs);
-    input_bias_ = InputBiasFrom<GType>(inputs, scope);
-    input_mean_ = InputMeanFrom<GType>(inputs, scope);
-    input_scale_ = InputScaleFrom<GType>(inputs, scope);
-    input_variance_ = InputVarianceFrom<GType>(inputs, scope);
-    epsilon_ = GetAttr<float>("epsilon", attrs);
-    momentum_ = GetAttr<float>("momentum", attrs);
-    //    is_test_ = GetAttr<bool>("is_test", attrs);
+                           const AttributeMap &attrs, const Scope &scope)
+      : ConvParam<Dtype>(inputs, outputs, attrs, scope) {
+    bias_ = OpParam::InputYFrom<GType>(inputs, scope);
+    axis_ = OpParam::GetAttr<int>("axis", attrs);
+    output_ = OpParam::OutFrom<GType>(outputs, scope);
+    input_bias_ = OpParam::InputBiasFrom<GType>(inputs, scope);
+    input_mean_ = OpParam::InputMeanFrom<GType>(inputs, scope);
+    input_scale_ = OpParam::InputScaleFrom<GType>(inputs, scope);
+    input_variance_ = OpParam::InputVarianceFrom<GType>(inputs, scope);
+    epsilon_ = OpParam::GetAttr<float>("epsilon", attrs);
+    momentum_ = OpParam::GetAttr<float>("momentum", attrs);
+    //    is_test_ = OpParam::GetAttr<bool>("is_test", attrs);
   }
   RType *Bias() const { return bias_; }
 
   const int &Axis() const { return axis_; }
 
-  const RType *Input() const { return input_; }
-
-  const RType *Filter() const { return filter_; }
-
   RType *Output() const { return output_; }
 
-  const vector<int> &Strides() const { return strides_; }
-
-  const vector<int> &Paddings() const { return paddings_; }
-
-  const vector<int> &Dilations() const { return dilations_; }
-
-  const int &Groups() const { return groups; }
-
   const RType *InputBias() const { return input_bias_; }
 
   const RType *InputMean() const { return input_mean_; }
@@ -1584,13 +1497,7 @@ class FusionConvAddBNReluParam : public OpParam {
  protected:
   RType *bias_;
   int axis_;
-  RType *input_;
   RType *output_;
-  RType *filter_;
-  vector<int> strides_;
-  vector<int> paddings_;
-  vector<int> dilations_;
-  int groups;
   RType *input_bias_;
   RType *input_mean_;
   RType *input_scale_;
@@ -1614,57 +1521,40 @@ class FusionConvAddBNReluParam : public OpParam {
 
 #ifdef FUSION_CONVBNADDRELU_OP
 template <typename Dtype>
-class FusionConvBNAddReluParam : public OpParam {
+class FusionConvBNAddReluParam : public ConvParam<Dtype> {
   typedef typename DtypeTensorTrait<Dtype>::gtype GType;
   typedef typename DtypeTensorTrait<Dtype>::rtype RType;
 
  public:
   FusionConvBNAddReluParam(const VariableNameMap &inputs,
                            const VariableNameMap &outputs,
-                           const AttributeMap &attrs, const Scope &scope) {
-    bias_ = InputYFrom<GType>(inputs, scope);
-    axis_ = GetAttr<int>("axis", attrs);
-    filter_ = FilterFrom<GType>(inputs, scope);
-    input_ = InputFrom<GType>(inputs, scope);
-    output_ = OutFrom<GType>(outputs, scope);
-    strides_ = GetAttr<vector<int>>("strides", attrs);
-    paddings_ = GetAttr<vector<int>>("paddings", attrs);
-    dilations_ = GetAttr<vector<int>>("dilations", attrs);
-    groups = GetAttr<int>("groups", attrs);
-    input_bias_ = InputBiasFrom<GType>(inputs, scope);
-    input_mean_ = InputMeanFrom<GType>(inputs, scope);
-    input_scale_ = InputScaleFrom<GType>(inputs, scope);
-    input_variance_ = InputVarianceFrom<GType>(inputs, scope);
-    epsilon_ = GetAttr<float>("epsilon", attrs);
-    momentum_ = GetAttr<float>("momentum", attrs);
-    keyBNY_ = getkey("BNY", inputs, 0);
-    keyX_ = getkey("X", inputs, 0);
-    keyY_ = getkey("Y", inputs, 0);
+                           const AttributeMap &attrs, const Scope &scope)
+      : ConvParam<Dtype>(inputs, outputs, attrs, scope) {
+    bias_ = OpParam::InputYFrom<GType>(inputs, scope);
+    axis_ = OpParam::GetAttr<int>("axis", attrs);
+    output_ = OpParam::OutFrom<GType>(outputs, scope);
+    input_bias_ = OpParam::InputBiasFrom<GType>(inputs, scope);
+    input_mean_ = OpParam::InputMeanFrom<GType>(inputs, scope);
+    input_scale_ = OpParam::InputScaleFrom<GType>(inputs, scope);
+    input_variance_ = OpParam::InputVarianceFrom<GType>(inputs, scope);
+    epsilon_ = OpParam::GetAttr<float>("epsilon", attrs);
+    momentum_ = OpParam::GetAttr<float>("momentum", attrs);
+    keyBNY_ = OpParam::getkey("BNY", inputs, 0);
+    keyX_ = OpParam::getkey("X", inputs, 0);
+    keyY_ = OpParam::getkey("Y", inputs, 0);
     if (keyX_ == keyBNY_) {
-      bias_ = InputYFrom<GType>(inputs, scope);
+      bias_ = OpParam::InputYFrom<GType>(inputs, scope);
     } else if (keyY_ == keyBNY_) {
-      bias_ = InputXFrom<GType>(inputs, scope);
+      bias_ = OpParam::InputXFrom<GType>(inputs, scope);
     }
-    //    is_test_ = GetAttr<bool>("is_test", attrs);
+    //    is_test_ = OpParam::GetAttr<bool>("is_test", attrs);
   }
   RType *Bias() const { return bias_; }
 
   const int &Axis() const { return axis_; }
 
-  const RType *Input() const { return input_; }
-
-  const RType *Filter() const { return filter_; }
-
   RType *Output() const { return output_; }
 
-  const vector<int> &Strides() const { return strides_; }
-
-  const vector<int> &Paddings() const { return paddings_; }
-
-  const vector<int> &Dilations() const { return dilations_; }
-
-  const int &Groups() const { return groups; }
-
   const RType *InputBias() const { return input_bias_; }
 
   const RType *InputMean() const { return input_mean_; }
@@ -1690,13 +1580,7 @@ class FusionConvBNAddReluParam : public OpParam {
  protected:
   RType *bias_;
   int axis_;
-  RType *input_;
   RType *output_;
-  RType *filter_;
-  vector<int> strides_;
-  vector<int> paddings_;
-  vector<int> dilations_;
-  int groups;
   RType *input_bias_;
   RType *input_mean_;
   RType *input_scale_;
@@ -1723,44 +1607,26 @@ class FusionConvBNAddReluParam : public OpParam {
 
 #ifdef FUSION_CONVBN_OP
 template <typename Dtype>
-class FusionConvBNParam : public OpParam {
+class FusionConvBNParam : public ConvParam<Dtype> {
   typedef typename DtypeTensorTrait<Dtype>::gtype GType;
   typedef typename DtypeTensorTrait<Dtype>::rtype RType;
 
  public:
   FusionConvBNParam(const VariableNameMap &inputs,
                     const VariableNameMap &outputs, const AttributeMap &attrs,
-                    const Scope &scope) {
-    filter_ = FilterFrom<GType>(inputs, scope);
-    input_ = InputFrom<GType>(inputs, scope);
-    output_y_ = OutputYFrom<GType>(outputs, scope);
-    strides_ = GetAttr<vector<int>>("strides", attrs);
-    paddings_ = GetAttr<vector<int>>("paddings", attrs);
-    dilations_ = GetAttr<vector<int>>("dilations", attrs);
-    groups = GetAttr<int>("groups", attrs);
-    input_bias_ = InputBiasFrom<GType>(inputs, scope);
-    input_mean_ = InputMeanFrom<GType>(inputs, scope);
-    input_scale_ = InputScaleFrom<GType>(inputs, scope);
-    input_variance_ = InputVarianceFrom<GType>(inputs, scope);
-    epsilon_ = GetAttr<float>("epsilon", attrs);
-    momentum_ = GetAttr<float>("momentum", attrs);
-    //    is_test_ = GetAttr<bool>("is_test", attrs);
+                    const Scope &scope)
+      : ConvParam<Dtype>(inputs, outputs, attrs, scope) {
+    output_y_ = OpParam::OutputYFrom<GType>(outputs, scope);
+    input_bias_ = OpParam::InputBiasFrom<GType>(inputs, scope);
+    input_mean_ = OpParam::InputMeanFrom<GType>(inputs, scope);
+    input_scale_ = OpParam::InputScaleFrom<GType>(inputs, scope);
+    input_variance_ = OpParam::InputVarianceFrom<GType>(inputs, scope);
+    epsilon_ = OpParam::GetAttr<float>("epsilon", attrs);
+    momentum_ = OpParam::GetAttr<float>("momentum", attrs);
+    //    is_test_ = OpParam::GetAttr<bool>("is_test", attrs);
   }
-
-  const RType *Input() const { return input_; }
-
-  const RType *Filter() const { return filter_; }
-
   RType *Output() const { return output_y_; }
 
-  const vector<int> &Strides() const { return strides_; }
-
-  const vector<int> &Paddings() const { return paddings_; }
-
-  const vector<int> &Dilations() const { return dilations_; }
-
-  const int &Groups() const { return groups; }
-
   const RType *InputBias() const { return input_bias_; }
 
   const RType *InputMean() const { return input_mean_; }
@@ -1784,13 +1650,7 @@ class FusionConvBNParam : public OpParam {
   const RType *NewBias() const { return new_bias_; }
 
  protected:
-  RType *input_;
   RType *output_y_;
-  RType *filter_;
-  vector<int> strides_;
-  vector<int> paddings_;
-  vector<int> dilations_;
-  int groups;
   RType *input_bias_;
   RType *input_mean_;
   RType *input_scale_;
@@ -1814,49 +1674,32 @@ class FusionConvBNParam : public OpParam {
 
 #ifdef FUSION_CONVADDBN_OP
 template <typename Dtype>
-class FusionConvAddBNParam : public OpParam {
+class FusionConvAddBNParam : public ConvParam<Dtype> {
   typedef typename DtypeTensorTrait<Dtype>::gtype GType;
   typedef typename DtypeTensorTrait<Dtype>::rtype RType;
 
  public:
   FusionConvAddBNParam(const VariableNameMap &inputs,
                        const VariableNameMap &outputs,
-                       const AttributeMap &attrs, const Scope &scope) {
-    bias_ = InputYFrom<GType>(inputs, scope);
-    axis_ = GetAttr<int>("axis", attrs);
-    filter_ = FilterFrom<GType>(inputs, scope);
-    input_ = InputFrom<GType>(inputs, scope);
-    output_y_ = OutputYFrom<GType>(outputs, scope);
-    strides_ = GetAttr<vector<int>>("strides", attrs);
-    paddings_ = GetAttr<vector<int>>("paddings", attrs);
-    dilations_ = GetAttr<vector<int>>("dilations", attrs);
-    groups = GetAttr<int>("groups", attrs);
-    input_bias_ = InputBiasFrom<GType>(inputs, scope);
-    input_mean_ = InputMeanFrom<GType>(inputs, scope);
-    input_scale_ = InputScaleFrom<GType>(inputs, scope);
-    input_variance_ = InputVarianceFrom<GType>(inputs, scope);
-    epsilon_ = GetAttr<float>("epsilon", attrs);
-    momentum_ = GetAttr<float>("momentum", attrs);
-    //    is_test_ = GetAttr<bool>("is_test", attrs);
+                       const AttributeMap &attrs, const Scope &scope)
+      : ConvParam<Dtype>(inputs, outputs, attrs, scope) {
+    bias_ = OpParam::InputYFrom<GType>(inputs, scope);
+    axis_ = OpParam::GetAttr<int>("axis", attrs);
+    output_y_ = OpParam::OutputYFrom<GType>(outputs, scope);
+    input_bias_ = OpParam::InputBiasFrom<GType>(inputs, scope);
+    input_mean_ = OpParam::InputMeanFrom<GType>(inputs, scope);
+    input_scale_ = OpParam::InputScaleFrom<GType>(inputs, scope);
+    input_variance_ = OpParam::InputVarianceFrom<GType>(inputs, scope);
+    epsilon_ = OpParam::GetAttr<float>("epsilon", attrs);
+    momentum_ = OpParam::GetAttr<float>("momentum", attrs);
+    //    is_test_ = OpParam::GetAttr<bool>("is_test", attrs);
   }
   RType *Bias() const { return bias_; }
 
   const int &Axis() const { return axis_; }
 
-  const RType *Input() const { return input_; }
-
-  const RType *Filter() const { return filter_; }
-
   RType *Output() const { return output_y_; }
 
-  const vector<int> &Strides() const { return strides_; }
-
-  const vector<int> &Paddings() const { return paddings_; }
-
-  const vector<int> &Dilations() const { return dilations_; }
-
-  const int &Groups() const { return groups; }
-
   const RType *InputBias() const { return input_bias_; }
 
   const RType *InputMean() const { return input_mean_; }
@@ -1882,13 +1725,7 @@ class FusionConvAddBNParam : public OpParam {
  protected:
   RType *bias_;
   int axis_;
-  RType *input_;
   RType *output_y_;
-  RType *filter_;
-  vector<int> strides_;
-  vector<int> paddings_;
-  vector<int> dilations_;
-  int groups;
   RType *input_bias_;
   RType *input_mean_;
   RType *input_scale_;
@@ -1912,44 +1749,26 @@ class FusionConvAddBNParam : public OpParam {
 
 #ifdef FUSION_DWCONVBNRELU_OP
 template <typename Dtype>
-class FusionDWConvBNReluParam : public OpParam {
+class FusionDWConvBNReluParam : public ConvParam<Dtype> {
   typedef typename DtypeTensorTrait<Dtype>::gtype GType;
   typedef typename DtypeTensorTrait<Dtype>::rtype RType;
 
  public:
   FusionDWConvBNReluParam(const VariableNameMap &inputs,
                           const VariableNameMap &outputs,
-                          const AttributeMap &attrs, const Scope &scope) {
-    filter_ = FilterFrom<GType>(inputs, scope);
-    input_ = InputFrom<GType>(inputs, scope);
-    output_ = OutFrom<GType>(outputs, scope);
-    strides_ = GetAttr<vector<int>>("strides", attrs);
-    paddings_ = GetAttr<vector<int>>("paddings", attrs);
-    dilations_ = GetAttr<vector<int>>("dilations", attrs);
-    groups = GetAttr<int>("groups", attrs);
-    input_bias_ = InputBiasFrom<GType>(inputs, scope);
-    input_mean_ = InputMeanFrom<GType>(inputs, scope);
-    input_scale_ = InputScaleFrom<GType>(inputs, scope);
-    input_variance_ = InputVarianceFrom<GType>(inputs, scope);
-    epsilon_ = GetAttr<float>("epsilon", attrs);
-    momentum_ = GetAttr<float>("momentum", attrs);
-    //    is_test_ = GetAttr<bool>("is_test", attrs);
+                          const AttributeMap &attrs, const Scope &scope)
+      : ConvParam<Dtype>(inputs, outputs, attrs, scope) {
+    output_ = OpParam::OutFrom<GType>(outputs, scope);
+    input_bias_ = OpParam::InputBiasFrom<GType>(inputs, scope);
+    input_mean_ = OpParam::InputMeanFrom<GType>(inputs, scope);
+    input_scale_ = OpParam::InputScaleFrom<GType>(inputs, scope);
+    input_variance_ = OpParam::InputVarianceFrom<GType>(inputs, scope);
+    epsilon_ = OpParam::GetAttr<float>("epsilon", attrs);
+    momentum_ = OpParam::GetAttr<float>("momentum", attrs);
+    //    is_test_ = OpParam::GetAttr<bool>("is_test", attrs);
   }
-
-  const RType *Input() const { return input_; }
-
-  const RType *Filter() const { return filter_; }
-
   RType *Output() const { return output_; }
 
-  const vector<int> &Strides() const { return strides_; }
-
-  const vector<int> &Paddings() const { return paddings_; }
-
-  const vector<int> &Dilations() const { return dilations_; }
-
-  const int &Groups() const { return groups; }
-
   const RType *InputBias() const { return input_bias_; }
 
   const RType *InputMean() const { return input_mean_; }
@@ -1973,13 +1792,7 @@ class FusionDWConvBNReluParam : public OpParam {
   const RType *NewBias() const { return new_bias_; }
 
  protected:
-  RType *input_;
   RType *output_;
-  RType *filter_;
-  vector<int> strides_;
-  vector<int> paddings_;
-  vector<int> dilations_;
-  int groups;
   RType *input_bias_;
   RType *input_mean_;
   RType *input_scale_;
@@ -1995,45 +1808,26 @@ class FusionDWConvBNReluParam : public OpParam {
 
 #ifdef FUSION_CONVBNRELU_OP
 template <typename Dtype>
-class FusionConvBNReluParam : public OpParam {
+class FusionConvBNReluParam : public ConvParam<Dtype> {
   typedef typename DtypeTensorTrait<Dtype>::gtype GType;
   typedef typename DtypeTensorTrait<Dtype>::rtype RType;
 
  public:
   FusionConvBNReluParam(const VariableNameMap &inputs,
                         const VariableNameMap &outputs,
-                        const AttributeMap &attrs, const Scope &scope) {
-    filter_ = FilterFrom<GType>(inputs, scope);
-    input_ = InputFrom<GType>(inputs, scope);
-    output_ = OutFrom<GType>(outputs, scope);
-
-    strides_ = GetAttr<vector<int>>("strides", attrs);
-    paddings_ = GetAttr<vector<int>>("paddings", attrs);
-    dilations_ = GetAttr<vector<int>>("dilations", attrs);
-    groups = GetAttr<int>("groups", attrs);
-    input_bias_ = InputBiasFrom<GType>(inputs, scope);
-    input_mean_ = InputMeanFrom<GType>(inputs, scope);
-    input_scale_ = InputScaleFrom<GType>(inputs, scope);
-    input_variance_ = InputVarianceFrom<GType>(inputs, scope);
-    epsilon_ = GetAttr<float>("epsilon", attrs);
-    momentum_ = GetAttr<float>("momentum", attrs);
-    //    is_test_ = GetAttr<bool>("is_test", attrs);
+                        const AttributeMap &attrs, const Scope &scope)
+      : ConvParam<Dtype>(inputs, outputs, attrs, scope) {
+    output_ = OpParam::OutFrom<GType>(outputs, scope);
+    input_bias_ = OpParam::InputBiasFrom<GType>(inputs, scope);
+    input_mean_ = OpParam::InputMeanFrom<GType>(inputs, scope);
+    input_scale_ = OpParam::InputScaleFrom<GType>(inputs, scope);
+    input_variance_ = OpParam::InputVarianceFrom<GType>(inputs, scope);
+    epsilon_ = OpParam::GetAttr<float>("epsilon", attrs);
+    momentum_ = OpParam::GetAttr<float>("momentum", attrs);
+    //    is_test_ = OpParam::GetAttr<bool>("is_test", attrs);
   }
-
-  const RType *Input() const { return input_; }
-
-  const RType *Filter() const { return filter_; }
-
   RType *Output() const { return output_; }
 
-  const vector<int> &Strides() const { return strides_; }
-
-  const vector<int> &Paddings() const { return paddings_; }
-
-  const vector<int> &Dilations() const { return dilations_; }
-
-  const int &Groups() const { return groups; }
-
   const RType *InputBias() const { return input_bias_; }
 
   const RType *InputMean() const { return input_mean_; }
@@ -2057,13 +1851,7 @@ class FusionConvBNReluParam : public OpParam {
   const RType *NewBias() const { return new_bias_; }
 
  protected:
-  RType *input_;
   RType *output_;
-  RType *filter_;
-  vector<int> strides_;
-  vector<int> paddings_;
-  vector<int> dilations_;
-  int groups;
   RType *input_bias_;
   RType *input_mean_;
   RType *input_scale_;