Samsung · hseok-oh · Jul 31, 2024 · Jul 30, 2024
diff --git a/runtime/onert/core/include/backend/basic/BackendContextHelpers.h b/runtime/onert/core/include/backend/basic/BackendContextHelpers.h
@@ -190,8 +190,6 @@ template <typename T_BackendContext> ITensorRegistry *genTensors(T_BackendContex
   graph.operands().iterate([&](const ir::OperandIndex &ind, const ir::Operand &obj) {
     if (ctx.external_operands().contains(ind))
       return;
-    // NOTE Assuming there is no layout changes (Always assume NHWC or UNKNOWN)
-    assert(graph.layout() != ir::Layout::NCHW);
     tensor_builder->registerTensorInfo(ind, obj.info());
   });
 

diff --git a/runtime/onert/core/include/backend/basic/train/TrainableBackendContextHelpers.h b/runtime/onert/core/include/backend/basic/train/TrainableBackendContextHelpers.h
@@ -39,8 +39,6 @@ ITensorRegistry *genTensors(backend::train::TrainableBackendContext &ctx,
   tgraph.operands().iterate([&](const ir::OperandIndex &ind, const ir::Operand &obj) {
     if (ctx.external_operands().contains(ind))
       return;
-    // NOTE Assuming there is no layout changes (Always assume NHWC or UNKNOWN)
-    assert(tgraph.layout() != ir::Layout::NCHW);
     tensor_builder->registerTensorInfo(ind, obj.info());
   });
 

diff --git a/runtime/onert/core/include/ir/Graph.h b/runtime/onert/core/include/ir/Graph.h
@@ -113,7 +113,6 @@ class Graph : public IGraph
   Operands &operands() { return _operands; } // TODO Remove this non-const accessor
   const Operations &operations() const override { return _operations; }
   Operations &operations() { return _operations; }
-  Layout layout() const { return _layout; }
 
   // Topological sort
 public:
@@ -126,8 +125,6 @@ class Graph : public IGraph
   OperandIndexSequence _outputs;
   std::unordered_map<std::string, IOIndex> _name_to_input;
   std::unordered_map<std::string, IOIndex> _name_to_output;
-  // TFLite and circle's default layout is NHWC;
-  Layout _layout{Layout::NHWC};
 };
 
 } // namespace ir

diff --git a/runtime/onert/core/include/ir/train/TrainableGraph.h b/runtime/onert/core/include/ir/train/TrainableGraph.h
@@ -125,7 +125,6 @@ class TrainableGraph : public IGraph
   const Operations &operations() const override { return _graph.operations(); }
   const Operands &backward_operands() const { return _backward_operands; }
   OperandIndex getLossIndex(const IOIndex &pred_io_ind) const;
-  Layout layout() const { return _graph.layout(); }
   const Graph &graph() const { return _graph; }
 
 public:

diff --git a/runtime/onert/core/include/util/ShapeInference.h b/runtime/onert/core/include/util/ShapeInference.h
@@ -27,7 +27,6 @@
 #include "ir/operation/StridedSlice.h"
 #include "compiler/LoweredGraph.h"
 #include "ir/Index.h"
-#include "ir/Layout.h"
 #include "ir/OperationVisitor.h"
 #include "backend/ITensor.h"
 #include "backend/ITensorRegistry.h"
@@ -58,12 +57,10 @@ ir::Shape inferBroadcastToShape(const ir::Shape shp_shape, const int32_t *shp_bu
 ir::Shape inferConcatShape(const Shapes &in_shapes, const ir::operation::Concat::Param &param);
 
 ir::Shape inferConv2DShape(const ir::Shape &in_shape, const ir::Shape &ker_shape,
-                           const ir::operation::Conv2D::Param &param,
-                           ir::Layout layout = ir::Layout::NHWC);
+                           const ir::operation::Conv2D::Param &param);
 
 ir::Shape inferDepthwiseConv2DShape(const ir::Shape &in_shape, const ir::Shape &ker_shape,
-                                    const ir::operation::DepthwiseConv2D::Param &param,
-                                    ir::Layout layout = ir::Layout::NHWC);
+                                    const ir::operation::DepthwiseConv2D::Param &param);
 
 ir::Shape inferEltwiseShape(const ir::Shape &lhs_shape, const ir::Shape &rhs_shape);
 
@@ -82,8 +79,7 @@ ir::Shape inferPackShape(const ir::Shape &input_shape, int axis, int rank, int n
 
 ir::Shape inferPadShape(const ir::Shape &in_shape, const int32_t *pad_buf, const size_t num_pads);
 
-ir::Shape inferPoolShape(const ir::Shape &in_shape, const ir::operation::Pool2D::Param &param,
-                         ir::Layout layout = ir::Layout::NHWC);
+ir::Shape inferPoolShape(const ir::Shape &in_shape, const ir::operation::Pool2D::Param &param);
 
 template <typename T> ir::Shape inferRangeShape(T start_val, T limit_val, T delta_val);
 

diff --git a/runtime/onert/core/src/compiler/ExecutorFactory.cc b/runtime/onert/core/src/compiler/ExecutorFactory.cc
@@ -111,7 +111,6 @@ void initializeSubgraphIOTensors(compiler::ILoweredGraph &lowered_graph,
   for (auto &&ind : indices)
   {
     const auto &operand = lowered_graph.graph().operands().at(ind);
-    assert(lowered_graph.graph().layout() == ir::Layout::NHWC);
     auto tensor = std::make_unique<backend::builtin::IOTensor>(operand.info());
 
     // Add tensor to builtin TensorRegistry.

diff --git a/runtime/onert/core/src/compiler/LoweredGraph.cc b/runtime/onert/core/src/compiler/LoweredGraph.cc
@@ -148,7 +148,7 @@ void LoweredGraph::makeLowerInfo(const compiler::BackendResolver &backend_resolv
 
   // Handle graph inputs and outputs
   const auto builtin_backend = BackendManager::get().getBuiltin();
-  auto factor = PermuteFactor{builtin_backend, _graph.layout()};
+  auto factor = PermuteFactor{builtin_backend, ir::Layout::NHWC};
   for (auto &&index : _graph.getInputs() | ir::Remove::UNDEFINED)
   {
     auto &operand_li = lower_info().operand.at(index);

diff --git a/runtime/onert/core/src/compiler/ShapeValidator.cc b/runtime/onert/core/src/compiler/ShapeValidator.cc
@@ -82,9 +82,8 @@ void ShapeValidator::visit(const ir::operation::BatchToSpaceND &node)
   const auto block_size_index{
     node.getInputs().at(ir::operation::BatchToSpaceND::Input::BLOCK_SIZE)};
 
-  const auto frontend_layout = _graph.layout();
-  const auto input_shape = operands.at(ifm_index).shape().asFeature(frontend_layout);
-  const auto output_shape = operands.at(ofm_index).shape().asFeature(frontend_layout);
+  const auto input_shape = operands.at(ifm_index).shape().asFeature(ir::Layout::NHWC);
+  const auto output_shape = operands.at(ofm_index).shape().asFeature(ir::Layout::NHWC);
 
   // All requirement as per NNAPI specification.
   OP_REQUIRES(operands.at(ifm_index).shape().rank() == 4);
@@ -392,9 +391,8 @@ void ShapeValidator::visit(const ir::operation::SpaceToBatchND &node)
     node.getInputs().at(ir::operation::SpaceToBatchND::Input::BLOCK_SIZE)};
   const auto paddings_index{node.getInputs().at(ir::operation::SpaceToBatchND::Input::PADDINGS)};
 
-  const auto frontend_layout = _graph.layout();
-  const auto input_shape = operands.at(ifm_index).shape().asFeature(frontend_layout);
-  const auto output_shape = operands.at(ofm_index).shape().asFeature(frontend_layout);
+  const auto input_shape = operands.at(ifm_index).shape().asFeature(ir::Layout::NHWC);
+  const auto output_shape = operands.at(ofm_index).shape().asFeature(ir::Layout::NHWC);
 
   // All requirement as per NNAPI specification.
   OP_REQUIRES(operands.at(ifm_index).shape().rank() == 4);
@@ -418,9 +416,8 @@ void ShapeValidator::visit(const ir::operation::SpaceToDepth &node)
 
   const auto ifm_index{node.getInputs().at(ir::operation::SpaceToDepth::Input::INPUT)};
 
-  const auto frontend_layout = _graph.layout();
-  const auto input_shape = operands.at(ifm_index).shape().asFeature(frontend_layout);
-  const auto output_shape = operands.at(ofm_index).shape().asFeature(frontend_layout);
+  const auto input_shape = operands.at(ifm_index).shape().asFeature(ir::Layout::NHWC);
+  const auto output_shape = operands.at(ofm_index).shape().asFeature(ir::Layout::NHWC);
   const auto block_size = node.param().block_size;
 
   // All assertions as per NNAPI specification.
@@ -540,9 +537,8 @@ void ShapeValidator::visit(const ir::operation::TransposeConv &node)
   OP_REQUIRES(operands.at(ofm_index).shape().rank() == operands.at(ifm_index).shape().rank());
   OP_REQUIRES(operands.at(ofm_index).shape().rank() == operands.at(ker_index).shape().rank());
 
-  const auto frontend_layout = _graph.layout();
-  const auto ofm_shape = operands.at(ofm_index).shape().asFeature(frontend_layout);
-  const auto ifm_shape = operands.at(ifm_index).shape().asFeature(frontend_layout);
+  const auto ofm_shape = operands.at(ofm_index).shape().asFeature(ir::Layout::NHWC);
+  const auto ifm_shape = operands.at(ifm_index).shape().asFeature(ir::Layout::NHWC);
   // The kernel has only IHWO layout on frontend
   // So ker_shape is treated here below
   // I -> N
@@ -587,9 +583,8 @@ void ShapeValidator::visit(const ir::operation::DepthToSpace &node)
 
   const auto input_index{node.getInputs().at(ir::operation::DepthToSpace::Input::INPUT)};
 
-  const auto frontend_layout = _graph.layout();
-  const auto output_shape = operands.at(output_index).shape().asFeature(frontend_layout);
-  const auto input_shape = operands.at(input_index).shape().asFeature(frontend_layout);
+  const auto output_shape = operands.at(output_index).shape().asFeature(ir::Layout::NHWC);
+  const auto input_shape = operands.at(input_index).shape().asFeature(ir::Layout::NHWC);
 
   OP_REQUIRES(operands.at(input_index).shape().rank() == 4);
   OP_REQUIRES(operands.at(output_index).shape().rank() == 4);

diff --git a/runtime/onert/core/src/compiler/StaticShapeInferer.cc b/runtime/onert/core/src/compiler/StaticShapeInferer.cc
@@ -851,8 +851,6 @@ void StaticShapeInferer::visit(const ir::operation::Pool2D &op)
 {
   auto &operands = _lowered_subg->graph().operands();
 
-  const auto layout = _lowered_subg->graph().layout();
-
   const auto input_idx{op.getInputs().at(ir::operation::Pool2D::Input::INPUT)};
   const auto &input = operands.at(input_idx);
   if (input.info().shape().rank() != 4)
@@ -863,7 +861,7 @@ void StaticShapeInferer::visit(const ir::operation::Pool2D &op)
   const auto output_idx = op.getOutputs().at(0);
   ir::Operand &output = operands.at(output_idx);
 
-  ir::Shape new_shape = shape_inference::inferPoolShape(input.info().shape(), op.param(), layout);
+  ir::Shape new_shape = shape_inference::inferPoolShape(input.info().shape(), op.param());
   output.info().shape(new_shape);
 }
 

diff --git a/runtime/onert/core/src/compiler/pass/PermutationOperationPass.cc b/runtime/onert/core/src/compiler/pass/PermutationOperationPass.cc
@@ -43,7 +43,7 @@ void PermutationOperationPass::applyExpandRanks(const Operation &node)
 
   assert(output.getDef().valid());
   const auto node_index = output.getDef();
-  const auto frontend_layout = _graph.layout();
+  const auto frontend_layout = ir::Layout::NHWC;
   const auto backend_layout = _lowered_graph.lower_info().operation.getRawPtr(node_index)->layout();
 
   if (frontend_layout == backend_layout)
@@ -86,7 +86,7 @@ void PermutationOperationPass::changeToKeepLayout(const Operation &node)
 
   auto &operation_li_map = _lowered_graph.lower_info().operation;
   auto &operand_li_map = _lowered_graph.lower_info().operand;
-  const auto frontend_layout = _graph.layout();
+  const auto frontend_layout = ir::Layout::NHWC;
   const auto backend_layout = operation_li_map.getRawPtr(node_index)->layout();
 
   if (frontend_layout == backend_layout)

diff --git a/runtime/onert/core/src/compiler/train/LoweredTrainableGraph.cc b/runtime/onert/core/src/compiler/train/LoweredTrainableGraph.cc
@@ -178,7 +178,7 @@ void LoweredTrainableGraph::makeLowerInfo(const compiler::BackendResolver &backe
 
   // Handle graph inputs and outputs
   const auto builtin_backend = BackendManager::get().getBuiltin();
-  auto factor = PermuteFactor{builtin_backend, _trainable_graph.layout()};
+  auto factor = PermuteFactor{builtin_backend, ir::Layout::NHWC};
   for (auto &&index : _trainable_graph.getInputs() | ir::Remove::UNDEFINED)
   {
     auto &operand_li = lower_info().operand.at(index);

diff --git a/runtime/onert/core/src/util/ShapeInference.cc b/runtime/onert/core/src/util/ShapeInference.cc
@@ -323,15 +323,15 @@ ir::Shape inferConcatShape(const Shapes &in_shapes, const ir::operation::Concat:
 }
 
 ir::Shape inferConv2DShape(const ir::Shape &in_shape, const ir::Shape &ker_shape,
-                           const ir::operation::Conv2D::Param &param, ir::Layout layout)
+                           const ir::operation::Conv2D::Param &param)
 {
   if (param.stride.horizontal == 0 || param.stride.vertical == 0)
     throw std::runtime_error{"Conv2D: stride values must be positive"};
 
-  auto ifm_shape = in_shape.asFeature(layout);
+  auto ifm_shape = in_shape.asFeature(ir::Layout::NHWC);
 
   // Kernel format is [depth_out, kernel_height, kernel_width, depth_in]
-  auto kf_shape = ker_shape.asFeature(layout);
+  auto kf_shape = ker_shape.asFeature(ir::Layout::NHWC);
   assert(ifm_shape.C == kf_shape.C);
 
   const auto [out_h, out_w] = calcConvLikeHeightAndWidth(
@@ -341,17 +341,15 @@ ir::Shape inferConv2DShape(const ir::Shape &in_shape, const ir::Shape &ker_shape
 }
 
 ir::Shape inferDepthwiseConv2DShape(const ir::Shape &in_shape, const ir::Shape &ker_shape,
-                                    const ir::operation::DepthwiseConv2D::Param &param,
-                                    ir::Layout layout)
+                                    const ir::operation::DepthwiseConv2D::Param &param)
 {
   if (param.stride.horizontal == 0 || param.stride.vertical == 0)
     throw std::runtime_error{"DepthwiseConv2D: stride values must be positive"};
 
-  assert(layout == ir::Layout::NHWC);
-  auto ifm_shape = in_shape.asFeature(layout);
+  auto ifm_shape = in_shape.asFeature(ir::Layout::NHWC);
 
   // Kernel format is [1, kernel_height, kernel_width, depth_out]
-  auto kf_shape = ker_shape.asFeature(layout);
+  auto kf_shape = ker_shape.asFeature(ir::Layout::NHWC);
   assert(kf_shape.C == static_cast<int32_t>(ifm_shape.C * param.multiplier));
   assert(kf_shape.N == 1);
 
@@ -546,14 +544,12 @@ ir::Shape inferPadShape(const ir::Shape &in_shape, const int32_t *pad_buf, const
   return ret;
 }
 
-ir::Shape inferPoolShape(const ir::Shape &in_shape, const ir::operation::Pool2D::Param &param,
-                         const ir::Layout layout)
+ir::Shape inferPoolShape(const ir::Shape &in_shape, const ir::operation::Pool2D::Param &param)
 {
   if (param.stride.horizontal == 0 || param.stride.vertical == 0)
     throw std::runtime_error{"Pool2D: stride values must be positive"};
 
-  assert(layout == ir::Layout::NHWC);
-  auto ifm_shape = in_shape.asFeature(layout);
+  auto ifm_shape = in_shape.asFeature(ir::Layout::NHWC);
   const auto [out_h, out_w] = calcConvLikeHeightAndWidth(ifm_shape.H, ifm_shape.W, param.kh,
                                                          param.kw, param.padding, param.stride);
   // Pooling don't change number of channels and batch size