add fusion bnrelu

src/operators/fusion_conv_add.h

@@ -68,11 +68,11 @@ class FusionConvAddOp : public framework::OperatorWithKernel<
 
 #ifdef PADDLE_MOBILE_CPU
 
-//#ifndef CONV_ADD_REGISTER
-//static framework::FusionOpRegistrar convadd_registrar(
-//    new FusionConvAddMatcher());
-//#define CONV_ADD_REGISTER
-//#endif
+#ifndef CONV_ADD_REGISTER
+static framework::FusionOpRegistrar convadd_registrar(
+    new FusionConvAddMatcher());
+#define CONV_ADD_REGISTER
+#endif
 
 #endif
 

src/operators/fusion_conv_add_bn_relu_op.h

@@ -80,7 +80,7 @@ class FusionConvAddBNReluOp
 #ifdef PADDLE_MOBILE_CPU
 
 #ifndef FUSION_CONV_ADD_BN_RELU_REGISTER
- static framework::FusionOpRegistrar fusion_conv_add_bn_relu_registrar(
+static framework::FusionOpRegistrar fusion_conv_add_bn_relu_registrar(
     new FusionConvAddBNReluMatcher());
 #define FUSION_CONV_ADD_BN_RELU_REGISTER
 #endif

src/operators/kernel/central-arm-func/conv_add_arm_func.h

@@ -125,10 +125,10 @@ void ConvAddCompute(const FusionConvAddParam &param) {
              param.Input()->dims()[1] == param.Output()->dims()[1] &&
              param.Filter()->dims()[2] == param.Filter()->dims()[3] &&
              param.Filter()->dims()[2] == 3 && param.Strides()[0] == 2) {
-//        math::DepthwiseConv3x3(param.Input(), param.Strides(),
-//        param.Paddings(),
-//                               param.Filter(), param.Bias(), param.Output(),
-//                               false);
+    //        math::DepthwiseConv3x3(param.Input(), param.Strides(),
+    //        param.Paddings(),
+    //                               param.Filter(), param.Bias(),
+    //                               param.Output(), false);
 
     math::DepthwiseConv3x3s2p1v2(param.Input(), param.Filter(), param.Output(),
                                  *param.Bias(), true);

src/operators/kernel/central-arm-func/conv_add_bn_relu_func.h

@@ -26,8 +26,6 @@ void ConvAddBNReluBasic(const FusionConvAddBNReluParam &param) {
   Tensor bias = *param.Bias();
   Tensor new_bias = *param.NewBias();
   Tensor new_scale = *param.NewScale();
-  auto new_bias_ptr = new_bias.data<float>();
-  auto new_scale_ptr = new_scale.data<float>();
   int axis = param.Axis();
   Tensor *output = param.Output();
   math::expand_bias(bias, axis, output->dims());
@@ -106,25 +104,12 @@ void ConvAddBNReluBasic(const FusionConvAddBNReluParam &param) {
       // gemm
       Tensor out_slice = out_batch.Slice(g * out_step, (g + 1) * out_step);
       Tensor filter_slice = filter.Slice(g * out_step, (g + 1) * out_step);
-//      math::matmul<float>(filter_slice, false, col_matrix, false,
-//                          static_cast<float>(1), &out_slice,
-//                          static_cast<float>(0));
-        math::matmulWithBn<float>(filter_slice, false, col_matrix, false,
-                          static_cast<float>(1), &out_slice,
-                          static_cast<float>(0),true, &new_scale,&new_bias);
+
+      math::matmulWithBn<float>(
+          filter_slice, false, col_matrix, false, static_cast<float>(1),
+          &out_slice, static_cast<float>(0), true, &new_scale, &new_bias);
     }
   }
-  /// todo : use neon in special case instead of 2for(300ms)
-//  auto output_ptr = output->data<float>();
-//  for (int c = 0; c < output_matrix_shape[0]; c++) {
-//    int start = c * output_matrix_shape[1];
-//    for (int j = 0; j < output_matrix_shape[1]; j++) {
-//      output_ptr[start + j] =
-//          output_ptr[start + j] * new_scale_ptr[c] + new_bias_ptr[c];
-//      output_ptr[start + j] =
-//          output_ptr[start + j] < 0 ? 0 : output_ptr[start + j];
-//    }
-//  }
 }
 template <typename P>
 void ConvAddBNReluCompute(const FusionConvAddBNReluParam &param) {

src/operators/math/math_function.h

@@ -30,7 +30,7 @@ void matmul(const framework::Tensor &matrix_a, bool trans_a,
 template <typename T>
 void matmulWithBn(const framework::Tensor &matrix_a, bool trans_a,
                   const framework::Tensor &matrix_b, bool trans_b, T alpha,
-                  framework::Tensor *matrix_out, T beta, bool relu = true,
+                  framework::Tensor *matrix_out, T beta, bool relu,
                   framework::Tensor *new_scale, framework::Tensor *new_bias);
 }  // namespace math
 }  // namespace operators

test/common/test_gemm.cpp

@@ -52,8 +52,9 @@ int main() {
   }
 
   auto time1 = time();
-//  paddle_mobile::operators::math::Sgemm(m, n, k, 0.9, a, lda, b, ldb, 0.3, c,
-//                                        ldc);
+  //  paddle_mobile::operators::math::Sgemm(m, n, k, 0.9, a, lda, b, ldb, 0.3,
+  //  c,
+  //                                        ldc);
   auto time2 = time();
   DLOG << "gemm cost :" << time_diff(time1, time2) << "ms\n";
   for (int i = 0; i < m * n; ++i) {