[moco-tf] Clean up trivials in FuseBinaryIntoPreceding (#6497)

This commit will clean up some codes
- Remove deprecated function
- Replace and correct comments
- Modify bracket formats

Signed-off-by: Seok NamKoong <sk.namkoong@samsung.com>

diff --git a/compiler/moco-tf/src/Transforms/FuseBinaryIntoPreceding.cpp b/compiler/moco-tf/src/Transforms/FuseBinaryIntoPreceding.cpp
index be5535e..67dab41 100644 (file)
--- a/compiler/moco-tf/src/Transforms/FuseBinaryIntoPreceding.cpp
+++ b/compiler/moco-tf/src/Transforms/FuseBinaryIntoPreceding.cpp
@@ -208,56 +208,6 @@ moco::tf::TFConst *create_kernel_from_fuse_mulparam<FuseType::DepthwiseConv2D>(
   return ker_fused;
 }
 
-// Will be deprecated
-moco::tf::TFConst *create_kernal_from_fuse_mulparam(loco::Graph *graph, moco::tf::TFConst *ker,
-                                                    moco::tf::TFConst *mulparam)
-{
-  auto ker_shape_inf = ker->annot<moco::tf::ShapeInferenceData>();
-  assert(ker_shape_inf);
-  auto ker_shape = ker_shape_inf->tensor_shape();
-
-  auto mulparam_shape_inf = mulparam->annot<moco::tf::ShapeInferenceData>();
-  assert(mulparam_shape_inf != nullptr);
-  auto mulparam_shape = mulparam_shape_inf->tensor_shape();
-
-  assert(ker_shape.rank() == 4);
-  assert(mulparam_shape.rank() == 1);
-  assert(ker_shape.dim(3).value() == mulparam_shape.dim(0).value());
-
-  // create new ker_fused with same size of ker
-  auto ker_fused = graph->nodes()->create<moco::tf::TFConst>();
-  ker_fused->dtype(loco::DataType::FLOAT32);
-  copy_shape(ker, ker_fused);
-  auto ker_num_elements = ker->size<loco::DataType::FLOAT32>();
-  ker_fused->size<loco::DataType::FLOAT32>(ker_num_elements);
-
-  // TensorFlow Kernel has HWIO format
-  // Broadcast Mul vector to Kernel tensor by the Output
-  const uint32_t ker_height = ker_shape.dim(0).value();
-  const uint32_t ker_width = ker_shape.dim(1).value();
-  const uint32_t ker_input = ker_shape.dim(2).value();
-  const uint32_t ker_output = ker_shape.dim(3).value();
-
-  for (uint32_t ker_y = 0; ker_y < ker_height; ++ker_y)
-  {
-    for (uint32_t ker_x = 0; ker_x < ker_width; ++ker_x)
-    {
-      for (uint32_t in_ch = 0; in_ch < ker_input; ++in_ch)
-      {
-        uint32_t num_items = ((ker_y * ker_width + ker_x) * ker_input + in_ch) * ker_output;
-        for (uint32_t out_ch = 0; out_ch < ker_output; ++out_ch)
-        {
-          auto mulparam_v = mulparam->at<loco::DataType::FLOAT32>(out_ch);
-          auto ker_v = ker->at<loco::DataType::FLOAT32>(num_items + out_ch);
-          ker_fused->at<loco::DataType::FLOAT32>(num_items + out_ch) = ker_v * mulparam_v;
-        }
-      }
-    }
-  }
-
-  return ker_fused;
-}
-
 /**
  * @brief Create a fused convolution opertion from kernel of fused mulparam
  * @return Fused convolution operation
@@ -353,7 +303,6 @@ bool fuse_to_preceding(loco::Graph *graph, moco::tf::TFMul *node)
 
   moco::tf::TFConst *mulparam = nullptr;
   moco::tf::TFNode *precedingOp = nullptr;
-  // TODO support FullyConnected
 
   if (xc != nullptr)
   {
@@ -368,6 +317,7 @@ bool fuse_to_preceding(loco::Graph *graph, moco::tf::TFMul *node)
 
   assert(mulparam->dtype() == loco::DataType::FLOAT32);
 
+  // TODO support FullyConnected
   moco::tf::TFNode *fused_node = nullptr;
   if (auto conv2d = dynamic_cast<moco::tf::TFConv2D *>(precedingOp))
     fused_node = fused_conv_node<FuseType::Conv2D, moco::tf::TFConv2D>(graph, mulparam, conv2d);
@@ -386,8 +336,8 @@ bool fuse_to_preceding(loco::Graph *graph, moco::tf::TFMul *node)
   // TODO check if need to disconnect
   // node->x(nullptr);
   // node->y(nullptr);
-  // conv2d->ifm(nullptr);
-  // conv2d->ker(nullptr);
+  // fused_node->ifm(nullptr);
+  // fused_node->ker(nullptr);
 
   return true;
 }
@@ -477,8 +427,6 @@ bool fuse_to_preceding(loco::Graph *graph, moco::tf::TFAdd *node)
 
   moco::tf::TFConst *addparam = nullptr;
   moco::tf::TFNode *precedingOp = nullptr;
-  moco::tf::TFBiasAdd *biasadd = nullptr;
-  // TODO support FullyConnected
 
   if (xc != nullptr)
   {
@@ -507,18 +455,14 @@ bool fuse_to_preceding(loco::Graph *graph, moco::tf::TFAdd *node)
     return false;
   }
 
+  // TODO support FullyConnected
+  moco::tf::TFBiasAdd *biasadd = nullptr;
   if (auto conv2d = dynamic_cast<moco::tf::TFConv2D *>(precedingOp))
-  {
     biasadd = create_biasadd_node<moco::tf::TFConv2D>(graph, addparam, conv2d);
-  }
   else if (auto dw_conv2d = dynamic_cast<moco::tf::TFDepthwiseConv2dNative *>(precedingOp))
-  {
     biasadd = create_biasadd_node<moco::tf::TFDepthwiseConv2dNative>(graph, addparam, dw_conv2d);
-  }
   else if (auto old_bias_add = dynamic_cast<moco::tf::TFBiasAdd *>(precedingOp))
-  {
     biasadd = old_bias_add;
-  }
 
   if (biasadd == nullptr)
   {