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//
// Copyright © 2018-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "BatchToSpaceNdLayer.hpp"
#include "LayerCloneBase.hpp"
#include <armnn/backends/WorkloadData.hpp>
#include <armnn/backends/WorkloadFactory.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 IWorkloadFactory& factory) const
{
BatchToSpaceNdQueueDescriptor descriptor;
SetAdditionalInfo(descriptor);
return factory.CreateWorkload(LayerType::BatchToSpaceNd, descriptor, PrepInfoAndDesc(descriptor));
}
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());
const TensorShape &outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
auto inferredShapes = InferOutputShapes({GetInputSlot(0).GetTensorInfo().GetShape()});
ARMNN_ASSERT(inferredShapes.size() == 1);
ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "BatchToSpaceNdLayer");
}
std::vector<TensorShape> BatchToSpaceNdLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
{
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<>());
outputShape[0] = (inputShape[0] / accumulatedBlockShape) < 1 ? 1 : (inputShape[0] / accumulatedBlockShape) ;
// In a 4D tensor, there will be 2 spatialDimensions (H and W), and the for loop will run twice.
// In a 3D tensor, there will be 1 spatialDimensions, and the for loop will run once.
unsigned int firstSpatialDimension = m_Param.m_DataLayout == DataLayout::NCHW ? 2 : 1;
for (unsigned int i = 0; i < m_Param.m_BlockShape.size(); ++i)
{
unsigned int spatialDimension = firstSpatialDimension + i;
unsigned int cropSize = m_Param.m_Crops[i].first + m_Param.m_Crops[i].second;
unsigned int outputSize = inputShape[spatialDimension] * m_Param.m_BlockShape[i];
outputShape[spatialDimension] = outputSize - cropSize;
}
return std::vector<TensorShape>({ outputShape });
}
void BatchToSpaceNdLayer::ExecuteStrategy(IStrategy& strategy) const
{
strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
}
} // namespace armnn
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