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//
// Copyright © 2017-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "PadLayer.hpp"
#include "LayerCloneBase.hpp"
#include <armnn/backends/TensorHandle.hpp>
#include <armnn/backends/WorkloadData.hpp>
#include <armnn/backends/WorkloadFactory.hpp>
#include <cstring>
namespace armnn
{
PadLayer::PadLayer(const armnn::PadDescriptor& param, const char* name)
: LayerWithParameters(1, 1, LayerType::Pad, param, name)
{}
std::unique_ptr<IWorkload> PadLayer::CreateWorkload(const armnn::IWorkloadFactory& factory) const
{
PadQueueDescriptor descriptor;
descriptor.m_Parameters.m_PadList = m_Param.m_PadList;
descriptor.m_Parameters.m_PaddingMode = m_Param.m_PaddingMode;
SetAdditionalInfo(descriptor);
return factory.CreateWorkload(LayerType::Pad, descriptor, PrepInfoAndDesc(descriptor));
}
PadLayer* PadLayer::Clone(Graph& graph) const
{
auto layer = CloneBase<PadLayer>(graph, m_Param, GetName());
layer->m_Param.m_PadList = m_Param.m_PadList;
layer->m_Param.m_PaddingMode = m_Param.m_PaddingMode;
return std::move(layer);
}
std::vector<TensorShape> PadLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
{
if (inputShapes.size() != 1)
{
throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
"\" - should be \"1\".");
}
const TensorShape& inputShape = inputShapes[0];
unsigned int rank = inputShape.GetNumDimensions();
if (m_Param.m_PadList.size() != rank)
{
throw armnn::Exception("Mismatch in size of mPadList and rank (\""
+ std::to_string(m_Param.m_PadList.size()) +
"\" vs "
+ std::to_string(rank) + ")");
}
if (rank == 0)
{
throw armnn::Exception("rank must not equal 0.");
}
std::vector<unsigned int> outputDimensionSizes(rank);
for (unsigned int i = 0; i < rank; ++i)
{
outputDimensionSizes[i] = inputShape[i] + m_Param.m_PadList[i].first + m_Param.m_PadList[i].second;
}
TensorShape tensorShape = TensorShape( rank, outputDimensionSizes.data());
return std::vector<TensorShape>({ tensorShape });
}
void PadLayer::ValidateTensorShapesFromInputs()
{
VerifyLayerConnections(1, CHECK_LOCATION());
const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetTensorInfo().GetShape() });
if (inferredShapes.size() != 1)
{
throw armnn::LayerValidationException("inferredShapes has "
+ std::to_string(inferredShapes.size()) +
" elements - should only have 1.");
}
ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "PadLayer");
}
void PadLayer::ExecuteStrategy(IStrategy& strategy) const
{
strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
}
} // namespace armnn
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