Remove `model::Shape::asVector` replacing calls to it with `num_elements()` or `dim...

Also remove unused `model::Shape::asMatrix` and `model::Shape::asTensor`.

This is a preparation step before removing dependency of `model::Shape` on `misc::tensor::Shape`.

Signed-off-by: Sergei Barannikov <s.barannikov@samsung.com>

diff --git a/runtimes/neurun/backend/acl_cl/StageGenerator.cc b/runtimes/neurun/backend/acl_cl/StageGenerator.cc
index 23bf4d9..9ba4c1a 100644 (file)
--- a/runtimes/neurun/backend/acl_cl/StageGenerator.cc
+++ b/runtimes/neurun/backend/acl_cl/StageGenerator.cc
@@ -908,9 +908,9 @@ void StageGenerator::visit(const model::operation::StridedSliceNode &node)
     auto startData_base = _ctx.at(startData_index).data().base();
     auto endData_base = _ctx.at(endData_index).data().base();
     auto stridesData_base = _ctx.at(stridesData_index).data().base();
-    const auto startData_size = _ctx.at(startData_index).shape().asVector();
-    const auto endData_size = _ctx.at(endData_index).shape().asVector();
-    const auto stridesData_size = _ctx.at(stridesData_index).shape().asVector();
+    const int startData_size = _ctx.at(startData_index).shape().num_elements();
+    const int endData_size = _ctx.at(endData_index).shape().num_elements();
+    const int stridesData_size = _ctx.at(stridesData_index).shape().num_elements();
 
     using neurun::model::DataType;
 
@@ -1012,7 +1012,7 @@ void StageGenerator::visit(const model::operation::TransposeNode &node)
   const auto rank = _ctx.at(ifm_idx).shape().rank();
   std::vector<int32_t> pv;
   const auto perm_base = _ctx.at(perm).data().base();
-  const auto perm_size = _ctx.at(perm).shape().asVector();
+  const int perm_size = _ctx.at(perm).shape().num_elements();
 
   assert(perm_base != nullptr);
   for (int32_t n = 0; n < perm_size; ++n)
@@ -1645,7 +1645,7 @@ void StageGenerator::visit(const model::operation::ReduceMaxNode &node)
       case 1: // vector
       {
         const auto axis_base = _ctx.at(axis_index).data().base();
-        const auto axis_size = _ctx.at(axis_index).shape().asVector();
+        const int axis_size = axis_shape.num_elements();
 
         // If axis's data does not exist as constant values and can be gotten as input data, we have
         // to find a way to infer output shape when sinking output.
@@ -2849,7 +2849,7 @@ void StageGenerator::visit(const model::operation::ArgMaxNode &node)
   _tensor_builder->dimCorrection(ifm_index, false);
 
   std::vector<uint32_t> l_axis;
-  const auto axis_size = _ctx.at(axis_index).shape().asVector();
+  const int axis_size = axis_shape.num_elements();
   auto axis_base = _ctx.at(axis_index).data().base();
   // TODO Should support axis size > 1.
   assert(axis_size == 1);
@@ -2984,7 +2984,7 @@ void StageGenerator::visit(const model::operation::MeanNode &node)
       case 1: // vector
       {
         const auto axis_base = _ctx.at(axis_index).data().base();
-        const auto axis_size = _ctx.at(axis_index).shape().asVector();
+        const int axis_size = axis_shape.num_elements();
 
         // If axis's data does not exist as constant values and can be gotten as input data, we have
         // to find a way to infer output shape when sinking output.
@@ -3192,7 +3192,7 @@ void StageGenerator::visit(const model::operation::ReduceMinNode &node)
       case 1: // vector
       {
         const auto axis_base = _ctx.at(axis_index).data().base();
-        const auto axis_size = _ctx.at(axis_index).shape().asVector();
+        const int axis_size = axis_shape.num_elements();
 
         // If axis's data does not exist as constant values and can be gotten as input data, we have
         // to find a way to infer output shape when sinking output.

diff --git a/runtimes/neurun/core/include/model/Shape.h b/runtimes/neurun/core/include/model/Shape.h
index 354f777..dd34074 100644 (file)
--- a/runtimes/neurun/core/include/model/Shape.h
+++ b/runtimes/neurun/core/include/model/Shape.h
@@ -40,10 +40,7 @@ public:
   Shape(const std::initializer_list<int32_t> &dims) : nnfw::misc::tensor::Shape(dims) {}
 
 public:
-  int32_t asVector(void) const;
-  nnfw::misc::matrix::Shape asMatrix(void) const;
   FeatureShape asFeature(Layout layout = Layout::NHWC) const;
-  nnfw::misc::tensor::Shape asTensor(void) const;
 
 public:
   /**

diff --git a/runtimes/neurun/core/include/util/Utils.h b/runtimes/neurun/core/include/util/Utils.h
index 2fb6893..debd950 100644 (file)
--- a/runtimes/neurun/core/include/util/Utils.h
+++ b/runtimes/neurun/core/include/util/Utils.h
@@ -57,7 +57,7 @@ void initConstant(neurun::backend::operand::IObject &obj, const neurun::model::O
     {
       case 1:
       {
-        auto vec_size = shape.asVector();
+        auto vec_size = shape.dim(0);
         for (int32_t n = 0; n < vec_size; ++n)
         {
           const T *from = reinterpret_cast<const T *>(base) + n;

diff --git a/runtimes/neurun/core/src/compiler/ConstantInitializer.cc b/runtimes/neurun/core/src/compiler/ConstantInitializer.cc
index 85967db..12fd143 100644 (file)
--- a/runtimes/neurun/core/src/compiler/ConstantInitializer.cc
+++ b/runtimes/neurun/core/src/compiler/ConstantInitializer.cc
@@ -48,7 +48,7 @@ void ConstantInitializer::run(neurun::backend::operand::IObject &obj,
     {
       case 1:
       {
-        auto vec_size = shape.asVector();
+        auto vec_size = shape.dim(0);
         for (int32_t n = 0; n < vec_size; ++n)
         {
           const T *from = reinterpret_cast<const T *>(base) + n;

diff --git a/runtimes/neurun/core/src/compiler/OperationValidator.cc b/runtimes/neurun/core/src/compiler/OperationValidator.cc
index 37672a5..e018b3d 100644 (file)
--- a/runtimes/neurun/core/src/compiler/OperationValidator.cc
+++ b/runtimes/neurun/core/src/compiler/OperationValidator.cc
@@ -141,16 +141,21 @@ void OperationValidator::visit(const model::operation::ReduceSumNode &node)
 
 void OperationValidator::visit(const model::operation::TransposeNode &node)
 {
-  const auto ofm_idx{node.getOutputs().at(0)};
-  const auto ifm_idx{node.getInputs().at(model::operation::TransposeNode::Input::INPUT)};
-  const auto perm{node.param().perm};
+  const auto output_index{node.getOutputs().at(0)};
+  const auto input_index{node.getInputs().at(model::operation::TransposeNode::Input::INPUT)};
+  const auto perm_idx{node.param().perm};
+
+  const auto &output_shape = _ctx.at(output_index).shape();
+  const auto &input_shape = _ctx.at(input_index).shape();
+  const auto &perm_shape = _ctx.at(perm_idx).shape();
 
-  UNUSED_RELEASE(ofm_idx);
-  UNUSED_RELEASE(ifm_idx);
-  UNUSED_RELEASE(perm);
+  UNUSED_RELEASE(output_shape);
+  UNUSED_RELEASE(input_shape);
+  UNUSED_RELEASE(perm_shape);
 
-  assert(_ctx.at(ifm_idx).shape().rank() == static_cast<uint32_t>(_ctx.at(perm).shape().dim(0)));
-  assert(_ctx.at(ifm_idx).shape().rank() == _ctx.at(ofm_idx).shape().rank());
+  assert(perm_shape.rank() == 1);
+  assert(input_shape.rank() == static_cast<uint32_t>(perm_shape.dim(0)));
+  assert(input_shape.rank() == output_shape.rank());
 }
 
 void OperationValidator::visit(const model::operation::ReduceMaxNode &node)

diff --git a/runtimes/neurun/core/src/model/Shape.cc b/runtimes/neurun/core/src/model/Shape.cc
index 12d7886..fd30882 100644 (file)
--- a/runtimes/neurun/core/src/model/Shape.cc
+++ b/runtimes/neurun/core/src/model/Shape.cc
@@ -29,23 +29,6 @@ Shape::Shape(uint32_t rank) : nnfw::misc::tensor::Shape(rank)
   // DO NOTHING
 }
 
-int32_t Shape::asVector(void) const
-{
-  assert(rank() == 1);
-
-  return dim(0);
-}
-
-nnfw::misc::matrix::Shape Shape::asMatrix(void) const
-{
-  assert(rank() == 2);
-
-  const auto height = dim(0);
-  const auto width = dim(1);
-
-  return nnfw::misc::matrix::Shape(height, width);
-}
-
 FeatureShape Shape::asFeature(const Layout layout) const
 {
   assert(rank() == 4);
@@ -66,17 +49,6 @@ FeatureShape Shape::asFeature(const Layout layout) const
   return FeatureShape(batch, depth, height, width);
 }
 
-nnfw::misc::tensor::Shape Shape::asTensor(void) const
-{
-  nnfw::misc::tensor::Shape shape{};
-  for (uint32_t i = 0; i < rank(); ++i)
-  {
-    shape.append(dim(i));
-  }
-
-  return shape; // this shape represents shape of NNAPI
-}
-
 // Extended dimension is filled with 1.
 void Shape::extendRank(size_t to_rank)
 {