Imported Upstream version 1.8.0

[platform/core/ml/nnfw.git] / runtime / onert / core / src / exec / DynamicShapeInference.cc

diff --git a/runtime/onert/core/src/exec/DynamicShapeInference.cc b/runtime/onert/core/src/exec/DynamicShapeInference.cc
index 1b82029..5ec7012 100644 (file)
--- a/runtime/onert/core/src/exec/DynamicShapeInference.cc
+++ b/runtime/onert/core/src/exec/DynamicShapeInference.cc
@@ -16,12 +16,21 @@
 
 #include "exec/DynamicShapeInference.h"
 #include "util/ShapeInference.h"
+#include <assert.h>
 
 namespace onert
 {
 namespace exec
 {
 
+inline backend::IDynamicTensorManager *
+dynamicTensorManagerOf(const std::shared_ptr<backend::ITensor> &tensor)
+{
+  if (!tensor->dynamic_tensor_manager())
+    throw std::runtime_error{"Dynamic Tensor Manager is not available for this tensor."};
+  return tensor->dynamic_tensor_manager();
+}
+
 void DynamicShapeInferer::handleBinaryArithmeticOp(const ir::Operation &op,
                                                    const ir::OperandIndex lhs_idx,
                                                    const ir::OperandIndex rhs_idx)
@@ -55,7 +64,7 @@ void DynamicShapeInferer::handleBinaryArithmeticOp(const ir::Operation &op,
 
   ir::Shape new_shape = shape_inference::inferEltwiseShape(lhs_shape, rhs_shape);
 
-  _dynamic_tensor_manager->applyShape(output_idx, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_idx, new_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -87,7 +96,7 @@ void DynamicShapeInferer::handleSimpleUnaryOp(const ir::Operation &op,
   auto output_ind = op.getOutputs().at(0);
   auto output = _tensor_registry->getITensor(output_ind);
 
-  _dynamic_tensor_manager->applyShape(output_ind, output_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, output_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -121,7 +130,7 @@ void DynamicShapeInferer::visit(const ir::operation::ArgMax &op)
 
   ir::Shape new_shape = shape_inference::inferArgMaxShape(input_shape, axis, rank);
 
-  _dynamic_tensor_manager->applyShape(output_ind, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, new_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -143,7 +152,7 @@ void DynamicShapeInferer::visit(const ir::operation::BatchMatMul &op)
   // TODO
 
   auto new_shape = shape_inference::inferBatchMatMulShape(lhs_shape, rhs_shape, op.param());
-  _dynamic_tensor_manager->applyShape(output_index, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_index, new_shape);
 }
 
 void DynamicShapeInferer::visit(const ir::operation::BroadcastTo &op)
@@ -166,7 +175,7 @@ void DynamicShapeInferer::visit(const ir::operation::BroadcastTo &op)
       shape->getShape(), reinterpret_cast<const int32_t *>(shape->buffer()));
 
   // set output shape and output buffer
-  _dynamic_tensor_manager->applyShape(output_ind, output_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, output_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -256,7 +265,7 @@ void DynamicShapeInferer::visit(const ir::operation::Concat &op)
   auto output = _tensor_registry->getITensor(output_ind);
   auto output_shape = shape_inference::inferConcatShape(in_shapes, op.param());
 
-  _dynamic_tensor_manager->applyShape(output_ind, output_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, output_shape);
 }
 
 void DynamicShapeInferer::visit(const ir::operation::Conv2D &op)
@@ -279,7 +288,7 @@ void DynamicShapeInferer::visit(const ir::operation::Conv2D &op)
 
   ir::Shape output_shape = shape_inference::inferConv2DShape(input_shape, ker_shape, op.param());
 
-  _dynamic_tensor_manager->applyShape(output_ind, output_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, output_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -339,7 +348,7 @@ void DynamicShapeInferer::visit(const ir::operation::ExpandDims &op)
 
   auto output_shape = shape_inference::inferExpandDimsShape(input_shape, axis_buf[0]);
 
-  _dynamic_tensor_manager->applyShape(output_ind, output_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, output_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -362,7 +371,7 @@ void DynamicShapeInferer::visit(const ir::operation::Fill &op)
 
   auto output_shape = shape_inference::inferFillShape(input_shape, input_buf);
 
-  _dynamic_tensor_manager->applyShape(output_ind, output_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, output_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -385,7 +394,7 @@ void DynamicShapeInferer::visit(const ir::operation::FullyConnected &op)
   auto output_ind = op.getOutputs().at(0);
   auto output = _tensor_registry->getITensor(output_ind);
 
-  _dynamic_tensor_manager->applyShape(output_ind, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, new_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -417,7 +426,7 @@ void DynamicShapeInferer::visit(const ir::operation::Gather &op)
   auto output_ind = op.getOutputs().at(0);
   auto output = _tensor_registry->getITensor(output_ind);
 
-  _dynamic_tensor_manager->applyShape(output_ind, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, new_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -442,6 +451,11 @@ void DynamicShapeInferer::visit(const ir::operation::Logistic &op)
   handleSimpleUnaryOp(op, op.getInputs().at(ir::operation::Logistic::INPUT));
 }
 
+void DynamicShapeInferer::visit(const ir::operation::L2Normalization &op)
+{
+  handleSimpleUnaryOp(op, op.getInputs().at(ir::operation::L2Normalization::INPUT));
+}
+
 void DynamicShapeInferer::visit(const ir::operation::MatrixBandPart &op)
 {
   handleSimpleUnaryOp(op, op.getInputs().at(ir::operation::MatrixBandPart::INPUT));
@@ -492,7 +506,7 @@ void DynamicShapeInferer::visit(const ir::operation::OneHot &op)
   const auto axis_val = op.param().axis;
 
   ir::Shape new_shape = shape_inference::inferOnehotShape(indices_shape, *depth_buf, axis_val);
-  _dynamic_tensor_manager->applyShape(output_ind, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, new_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -528,7 +542,7 @@ void DynamicShapeInferer::visit(const ir::operation::Pack &op)
 
   ir::Shape new_shape = shape_inference::inferPackShape(input_shape, axis, rank, num);
 
-  _dynamic_tensor_manager->applyShape(output_ind, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, new_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -555,7 +569,7 @@ void DynamicShapeInferer::visit(const ir::operation::Pad &op)
       shape_inference::inferPadShape(input->getShape(), pad_buf, pad->getShape().num_elements());
 
   // change output shape and reallocate output tensor memory
-  _dynamic_tensor_manager->applyShape(output_ind, output_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, output_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -607,7 +621,7 @@ void DynamicShapeInferer::visit(const ir::operation::Range &op)
         *reinterpret_cast<int32_t *>(limit_tensor->buffer()),
         *reinterpret_cast<int32_t *>(delta_tensor->buffer()));
   }
-  _dynamic_tensor_manager->applyShape(output_ind, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, new_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -651,7 +665,7 @@ void DynamicShapeInferer::visit(const ir::operation::Reduce &op)
 
   ir::Shape new_shape = shape_inference::inferReduceShape(input_shape, axes_vec, keep_dims);
 
-  _dynamic_tensor_manager->applyShape(output_ind, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, new_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -705,7 +719,7 @@ void DynamicShapeInferer::visit(const ir::operation::Reshape &op)
     if (output_shape != output->getShape() || output->buffer() == nullptr)
     {
       // change on output shape
-      _dynamic_tensor_manager->applyShape(output_ind, output_shape);
+      dynamicTensorManagerOf(output)->applyShape(output_ind, output_shape);
     }
     assert(output->buffer() != nullptr);
   }
@@ -721,7 +735,7 @@ void DynamicShapeInferer::visit(const ir::operation::Reshape &op)
     if (output_shape != output->getShape() || output->buffer() == nullptr)
     {
       // change on output shape
-      _dynamic_tensor_manager->applyShape(output_ind, output_shape);
+      dynamicTensorManagerOf(output)->applyShape(output_ind, output_shape);
     }
     assert(output->buffer() != nullptr);
   }
@@ -732,6 +746,31 @@ void DynamicShapeInferer::visit(const ir::operation::Reshape &op)
   }
 }
 
+void DynamicShapeInferer::visit(const ir::operation::ResizeBilinear &op)
+{
+  // check if output is not dynamic
+  auto output_ind = op.getOutputs().at(0);
+  auto output = _tensor_registry->getITensor(output_ind);
+
+  auto input_ind = op.getInputs().at(ir::operation::Reshape::Input::INPUT);
+  auto input = _tensor_registry->getITensor(input_ind);
+
+  if ((!input->is_dynamic()) && (!output->is_dynamic()))
+    return;
+
+  // getting output shape from input shape and Params
+  auto output_shape = shape_inference::inferResizeBilinearShape(
+      input->getShape(), op.param().height_out, op.param().width_out);
+
+  // if shape is changed, change output shape and reallocate output tensor memory
+  if (output_shape != output->getShape() || output->buffer() == nullptr)
+  {
+    // change on output shape
+    _dynamic_tensor_manager->applyShape(output_ind, output_shape);
+  }
+  assert(output->buffer() != nullptr);
+}
+
 void DynamicShapeInferer::visit(const ir::operation::Reverse &op)
 {
   handleSimpleUnaryOp(op, op.getInputs().at(ir::operation::Reverse::INPUT));
@@ -774,7 +813,7 @@ void DynamicShapeInferer::visit(const ir::operation::Select &op)
   auto output_ind = op.getOutputs().at(0);
   auto output = _tensor_registry->getITensor(output_ind);
 
-  _dynamic_tensor_manager->applyShape(output_ind, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, new_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -793,7 +832,7 @@ void DynamicShapeInferer::visit(const ir::operation::Shape &op)
   ir::Shape output_shape;
   output_shape.append(input_shape.rank());
 
-  _dynamic_tensor_manager->applyShape(output_ind, output_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, output_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -824,7 +863,7 @@ void DynamicShapeInferer::visit(const ir::operation::Slice &op)
 
   ir::Shape new_shape = shape_inference::inferSliceShape(input_shape, begins_buf, sizes_buf);
 
-  _dynamic_tensor_manager->applyShape(output_index, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_index, new_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -861,7 +900,7 @@ void DynamicShapeInferer::visit(const ir::operation::SpaceToBatchND &op)
   ir::Shape new_shape = shape_inference::inferSpaceToBatchNDShape(
       input_shape, block_shape_shape, padding_shape, block_shape_data, padding_data);
 
-  _dynamic_tensor_manager->applyShape(output_idx, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_idx, new_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -890,7 +929,7 @@ void DynamicShapeInferer::visit(const ir::operation::Split &op)
     auto output_ind = op.getOutputs().at(out_tensor_idx);
     auto output = _tensor_registry->getITensor(output_ind);
 
-    _dynamic_tensor_manager->applyShape(output_ind, new_shape);
+    dynamicTensorManagerOf(output)->applyShape(output_ind, new_shape);
     assert(output->buffer() != nullptr);
   }
 }
@@ -919,7 +958,7 @@ void DynamicShapeInferer::visit(const ir::operation::Squeeze &op)
   auto output_ind = op.getOutputs().at(0);
   auto output = _tensor_registry->getITensor(output_ind);
 
-  _dynamic_tensor_manager->applyShape(output_ind, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, new_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -960,7 +999,7 @@ void DynamicShapeInferer::visit(const ir::operation::StridedSlice &op)
   ir::Shape output_shape =
       onert::shape_inference::inferStridedSliceShape(input_shape, op_params, rank);
 
-  _dynamic_tensor_manager->applyShape(output_index, output_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_index, output_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -996,7 +1035,7 @@ void DynamicShapeInferer::visit(const ir::operation::Tile &op)
   auto output_shape = shape_inference::inferTileShape(input_shape, multiplier_buffer);
 
   // set output shape and output buffer
-  _dynamic_tensor_manager->applyShape(output_ind, output_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, output_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -1018,7 +1057,7 @@ void DynamicShapeInferer::visit(const ir::operation::Transpose &op)
   // set output shape, based on input and params
   ir::Shape new_shape = shape_inference::inferTransposeShape(input_shape, perm);
 
-  _dynamic_tensor_manager->applyShape(output_ind, new_shape);
+  dynamicTensorManagerOf(output)->applyShape(output_ind, new_shape);
   assert(output->buffer() != nullptr);
 }
 
@@ -1046,7 +1085,7 @@ void DynamicShapeInferer::visit(const ir::operation::Unpack &op)
     auto output_ind = op.getOutputs().at(out_tensor_idx);
     auto output = _tensor_registry->getITensor(output_ind);
 
-    _dynamic_tensor_manager->applyShape(output_ind, new_shape);
+    dynamicTensorManagerOf(output)->applyShape(output_ind, new_shape);
 
     assert(output->buffer() != nullptr);
   }