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//
// Copyright © 2018-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "SpaceToBatchNdLayer.hpp"
#include "LayerCloneBase.hpp"
#include <armnn/backends/WorkloadData.hpp>
#include <armnn/backends/WorkloadFactory.hpp>
#include <numeric>
using namespace armnnUtils;
namespace armnn
{
SpaceToBatchNdLayer::SpaceToBatchNdLayer(const SpaceToBatchNdDescriptor param, const char* name)
: LayerWithParameters(1, 1, LayerType::SpaceToBatchNd, param, name)
{}
std::unique_ptr<IWorkload> SpaceToBatchNdLayer::CreateWorkload(const IWorkloadFactory& factory) const
{
SpaceToBatchNdQueueDescriptor descriptor;
descriptor.m_Parameters.m_BlockShape = m_Param.m_BlockShape;
descriptor.m_Parameters.m_PadList = m_Param.m_PadList;
SetAdditionalInfo(descriptor);
return factory.CreateWorkload(LayerType::SpaceToBatchNd, descriptor, PrepInfoAndDesc(descriptor));
}
SpaceToBatchNdLayer* SpaceToBatchNdLayer::Clone(Graph& graph) const
{
IgnoreUnused(graph);
return CloneBase<SpaceToBatchNdLayer>(graph, m_Param, GetName());
}
std::vector<TensorShape> SpaceToBatchNdLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
{
const TensorShape inputShape = inputShapes[0];
TensorShape outputShape(inputShape);
outputShape[0] = inputShape[0] * std::accumulate(m_Param.m_BlockShape.begin(),
m_Param.m_BlockShape.end(),
1U,
std::multiplies<>());
// 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;
outputShape[spatialDimension] =
(inputShape[spatialDimension] + m_Param.m_PadList[i].first + m_Param.m_PadList[i].second)
/ m_Param.m_BlockShape[i];
}
return std::vector<TensorShape>({ outputShape });
}
void SpaceToBatchNdLayer::ValidateTensorShapesFromInputs()
{
VerifyLayerConnections(1, CHECK_LOCATION());
const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
std::vector<TensorShape> 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, "SpaceToBatchNdLayer");
}
void SpaceToBatchNdLayer::ExecuteStrategy(IStrategy& strategy) const
{
strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
}
} // namespace
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