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Diffstat (limited to 'src/armnn/layers/SpaceToDepthLayer.cpp')
| -rw-r--r-- | src/armnn/layers/SpaceToDepthLayer.cpp | 85 |
1 files changed, 85 insertions, 0 deletions
diff --git a/src/armnn/layers/SpaceToDepthLayer.cpp b/src/armnn/layers/SpaceToDepthLayer.cpp new file mode 100644 index 0000000000..b24490f82f --- /dev/null +++ b/src/armnn/layers/SpaceToDepthLayer.cpp @@ -0,0 +1,85 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "SpaceToDepthLayer.hpp" + +#include "LayerCloneBase.hpp" + +#include <armnn/TypesUtils.hpp> + +#include <backendsCommon/WorkloadData.hpp> +#include <backendsCommon/WorkloadFactory.hpp> + +#include <DataLayoutIndexed.hpp> + +#include <numeric> + +using namespace armnnUtils; + +namespace armnn +{ + +SpaceToDepthLayer::SpaceToDepthLayer(const SpaceToDepthDescriptor param, const char* name) + : LayerWithParameters(1, 1, LayerType::SpaceToDepth, param, name) +{} + +std::unique_ptr<IWorkload> SpaceToDepthLayer::CreateWorkload(const Graph& graph, + const IWorkloadFactory& factory) const +{ + SpaceToDepthQueueDescriptor descriptor; + descriptor.m_Parameters.m_BlockSize = m_Param.m_BlockSize; + descriptor.m_Parameters.m_DataLayout = m_Param.m_DataLayout; + + return factory.CreateSpaceToDepth(descriptor, PrepInfoAndDesc(descriptor, graph)); +} + +SpaceToDepthLayer* SpaceToDepthLayer::Clone(Graph& graph) const +{ + return CloneBase<SpaceToDepthLayer>(graph, m_Param, GetName()); +} + +std::vector<TensorShape> SpaceToDepthLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const +{ + BOOST_ASSERT(inputShapes.size() == 1); + + TensorShape inputShape = inputShapes[0]; + TensorShape outputShape(inputShape); + + outputShape[0] = inputShape[0]; + + DataLayoutIndexed dimensionIndices{m_Param.m_DataLayout}; + unsigned int hIndex = dimensionIndices.GetHeightIndex(); + unsigned int wIndex = dimensionIndices.GetWidthIndex(); + unsigned int cIndex = dimensionIndices.GetChannelsIndex(); + + outputShape[hIndex] = inputShape[hIndex] / m_Param.m_BlockSize; + outputShape[wIndex] = inputShape[wIndex] / m_Param.m_BlockSize; + + outputShape[cIndex] = inputShape[cIndex] * m_Param.m_BlockSize * m_Param.m_BlockSize; + + return std::vector<TensorShape>({ outputShape }); +} + +void SpaceToDepthLayer::ValidateTensorShapesFromInputs() +{ + VerifyLayerConnections(1, CHECK_LOCATION()); + + std::vector<TensorShape> inferredShapes = InferOutputShapes({ + GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape() }); + + BOOST_ASSERT(inferredShapes.size() == 1); + + ConditionalThrowIfNotEqual<LayerValidationException>( + "SpaceToDepthLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.", + GetOutputSlot(0).GetTensorInfo().GetShape(), + inferredShapes[0]); +} + +void SpaceToDepthLayer::Accept(ILayerVisitor& visitor) const +{ + visitor.VisitSpaceToDepthLayer(this, GetParameters(), GetName()); +} + +} // namespace armnn
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