adjust code style

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

@@ -32,12 +32,7 @@ void ConvAddReluCompute(const FusionConvAddReluParam &param) {
   Tensor bias = *param.Bias();
   int axis = param.Axis();
   Tensor *output = param.Output();
-  //  math::expand_bias(bias, axis, output->dims());
-  float *output_data = output->data<float>();
   float *biase_data = bias.data<float>();
-  //  for (int k = 0; k < output->numel(); ++k) {
-  //    output_data[k] = biase_data[k];
-  //  }
 
   int groups = param.Groups();
   std::vector<int> strides = param.Strides();

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

@@ -30,7 +30,6 @@ inline void ConvBasic(const ConvParam &param) {
   Tensor filter = *param.Filter();
   Tensor *output = param.Output();
   output->mutable_data<float>();
-  float *bias_data = output->mutable_data<float>();
   int groups = param.Groups();
   std::vector<int> strides = param.Strides();
   std::vector<int> paddings = param.Paddings();
@@ -107,7 +106,7 @@ inline void ConvBasic(const ConvParam &param) {
       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), false, bias_data);
+                          static_cast<float>(0));
     }
   }
 }

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

@@ -55,9 +55,9 @@ void FusionFcCompute(const FusionFcParam &param) {
     memory::Copy(out_data + i * classes, input_z_data, sizeof(float) * classes);
   }
 
-  //  for (int i = 0; i < out->numel(); i++) {
-  //    DLOG << out_data[i];
-  //  }
+  for (int i = 0; i < out->numel(); i++) {
+    DLOG << out_data[i];
+  }
   math::matmul<float>(x_matrix, false, y_matrix, false, static_cast<float>(1),
                       out, static_cast<float>(1), false, bias_data);
   PADDLE_MOBILE_ENFORCE(out_dim.size() == 2, " out_dim.size must be 2.");

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

@@ -59,7 +59,6 @@ void MulCompute(const MulParam &param) {
   const Tensor *input_y = param.InputY();
   Tensor *out = param.Out();
   out->mutable_data<float>();
-  float *bias_data = out->mutable_data<float>();
   const Tensor x_matrix =
       input_x->dims().size() > 2
           ? framework::ReshapeToMatrix(*input_x, param.XNumColDims())
@@ -73,7 +72,7 @@ void MulCompute(const MulParam &param) {
     out->Resize({x_matrix.dims()[0], y_matrix.dims()[1]});
   }
   math::matmul<float>(x_matrix, false, y_matrix, false, static_cast<float>(1),
-                      out, static_cast<float>(0), false, bias_data);
+                      out, static_cast<float>(0));
   if (out_dim.size() != 2) {
     out->Resize(out_dim);
   }

src/operators/math/gemm.cpp

@@ -373,9 +373,9 @@ void InnerKernel(int mc, int nc, float alpha, const float *a, const float *b,
 #endif
     }
   }
+
   if (alpha != 1) {
     WriteWithAlphaBeta(mc, nc, c, C, ldc);
-
     return;
   }
   if (beta == 0) {