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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "BatchToSpaceNdLayer.hpp"
#include "LayerCloneBase.hpp"
#include "LayerWithParameters.hpp"
#include "BatchToSpaceNdLayer.hpp"
#include <armnn/TypesUtils.hpp>
#include <backendsCommon/CpuTensorHandle.hpp>
#include <backendsCommon/WorkloadData.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
#include <DataLayoutIndexed.hpp>
#include <numeric>
using namespace armnnUtils;
namespace armnn
{
BatchToSpaceNdLayer::BatchToSpaceNdLayer(const armnn::BatchToSpaceNdDescriptor& param, const char* name)
: LayerWithParameters(1, 1, LayerType::BatchToSpaceNd, param, name)
{
}
std::unique_ptr<IWorkload> BatchToSpaceNdLayer::CreateWorkload(const Graph& graph,
const IWorkloadFactory& factory) const
{
BatchToSpaceNdQueueDescriptor descriptor;
return factory.CreateBatchToSpaceNd(descriptor, PrepInfoAndDesc(descriptor, graph));
}
BatchToSpaceNdLayer* BatchToSpaceNdLayer::Clone(Graph& graph) const
{
auto layer = CloneBase<BatchToSpaceNdLayer>(graph, m_Param, GetName());
return std::move(layer);
}
void BatchToSpaceNdLayer::ValidateTensorShapesFromInputs()
{
VerifyLayerConnections(1, CHECK_LOCATION());
auto inferredShapes = InferOutputShapes({GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape()});
BOOST_ASSERT(inferredShapes.size() == 1);
ConditionalThrowIfNotEqual<LayerValidationException>(
"BatchToSpaceLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
GetOutputSlot(0).GetTensorInfo().GetShape(),inferredShapes[0]);
}
std::vector<TensorShape> BatchToSpaceNdLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
{
BOOST_ASSERT(inputShapes.size() == 1);
const TensorShape& inputShape = inputShapes[0];
TensorShape outputShape(inputShape);
unsigned int accumulatedBlockShape = std::accumulate(m_Param.m_BlockShape.begin(),
m_Param.m_BlockShape.end(),
1U,
std::multiplies<>());
BOOST_ASSERT(inputShape[0] % accumulatedBlockShape == 0);
outputShape[0] = inputShape[0] / accumulatedBlockShape;
DataLayoutIndexed dimensionIndices = m_Param.m_DataLayout;
unsigned int heightIndex = dimensionIndices.GetHeightIndex();
unsigned int widthIndex = dimensionIndices.GetWidthIndex();
unsigned int heightCrop = m_Param.m_Crops[0].first + m_Param.m_Crops[0].second;
unsigned int widthCrop = m_Param.m_Crops[1].first + m_Param.m_Crops[1].second;
unsigned int outputHeight = inputShape[heightIndex] * m_Param.m_BlockShape[0];
unsigned int outputWidth = inputShape[widthIndex] * m_Param.m_BlockShape[1];
BOOST_ASSERT_MSG(heightCrop <= outputHeight,
"BatchToSpaceLayer: Overall height crop should be less than or equal to the uncropped output height.");
BOOST_ASSERT_MSG(widthCrop <= outputWidth,
"BatchToSpaceLayer: Overall width crop should be less than or equal to the uncropped output width.");
outputShape[heightIndex] = outputHeight - heightCrop;
outputShape[widthIndex] = outputWidth - widthCrop;
return std::vector<TensorShape>({ outputShape });
}
void BatchToSpaceNdLayer::Accept(ILayerVisitor& visitor) const
{
visitor.VisitBatchToSpaceNdLayer(this, GetParameters(), GetName());
}
} // namespace armnn
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