diff options
Diffstat (limited to 'src/armnn/layers/DepthToSpaceLayer.cpp')
-rw-r--r-- | src/armnn/layers/DepthToSpaceLayer.cpp | 84 |
1 files changed, 84 insertions, 0 deletions
diff --git a/src/armnn/layers/DepthToSpaceLayer.cpp b/src/armnn/layers/DepthToSpaceLayer.cpp new file mode 100644 index 0000000000..e964c32865 --- /dev/null +++ b/src/armnn/layers/DepthToSpaceLayer.cpp @@ -0,0 +1,84 @@ +// +// Copyright © 2019 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "DepthToSpaceLayer.hpp" + +#include "LayerCloneBase.hpp" + +#include <armnn/TypesUtils.hpp> + +#include <backendsCommon/WorkloadData.hpp> +#include <backendsCommon/WorkloadFactory.hpp> + +#include <DataLayoutIndexed.hpp> + +#include <numeric> + +namespace armnn +{ + +DepthToSpaceLayer::DepthToSpaceLayer(const DepthToSpaceDescriptor& param, const char* name) + : LayerWithParameters(1, 1, LayerType::DepthToSpace, param, name) +{} + +std::unique_ptr<IWorkload> DepthToSpaceLayer::CreateWorkload(const Graph& graph, + const IWorkloadFactory& factory) const +{ + DepthToSpaceQueueDescriptor descriptor; + descriptor.m_Parameters.m_BlockSize = m_Param.m_BlockSize; + descriptor.m_Parameters.m_DataLayout = m_Param.m_DataLayout; + + return factory.CreateDepthToSpace(descriptor, PrepInfoAndDesc(descriptor, graph)); +} + +DepthToSpaceLayer* DepthToSpaceLayer::Clone(Graph& graph) const +{ + return CloneBase<DepthToSpaceLayer>(graph, m_Param, GetName()); +} + +std::vector<TensorShape> DepthToSpaceLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const +{ + throw UnimplementedException("DepthToSpaceLayer::InferOutputShapes is not implemented"); + + BOOST_ASSERT(inputShapes.size() == 1); + + TensorShape inputShape = inputShapes[0]; + TensorShape outputShape(inputShape); + + armnnUtils::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 DepthToSpaceLayer::ValidateTensorShapesFromInputs() +{ + VerifyLayerConnections(1, CHECK_LOCATION()); + + std::vector<TensorShape> inferredShapes = InferOutputShapes({ + GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape() }); + + BOOST_ASSERT(inferredShapes.size() == 1); + + ConditionalThrowIfNotEqual<LayerValidationException>( + "DepthToSpaceLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.", + GetOutputSlot(0).GetTensorInfo().GetShape(), + inferredShapes[0]); +} + +void DepthToSpaceLayer::Accept(ILayerVisitor& visitor) const +{ + visitor.VisitDepthToSpaceLayer(this, GetParameters(), GetName()); +} + +} // namespace armnn |