PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteType > Class Template Reference

Replaces Permute leading into BatchToSpace with a DepthToSpace in the case where the Permute swaps the batch and channels dimensions such that the replacement is valid. More...

#include <PermuteAndBatchToSpaceAsDepthToSpace.hpp>

Public Member Functions
void	Run (Graph &graph, InputSlot &connection) const

Detailed Description

template<typename PermuteType>
class armnn::optimizations::PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteType >

Replaces Permute leading into BatchToSpace with a DepthToSpace in the case where the Permute swaps the batch and channels dimensions such that the replacement is valid.

Definition at line 18 of file PermuteAndBatchToSpaceAsDepthToSpace.hpp.

Member Function Documentation

Run()

template<typename PermuteType >

void Run ( Graph & graph, InputSlot & connection ) const

inline

Definition at line 21 of file PermuteAndBatchToSpaceAsDepthToSpace.hpp.

    {
        // Validate base layer (the Permute) is compatible
        Layer& base = connection.GetConnectedOutputSlot()->GetOwningLayer();
        ARMNN_ASSERT(base.GetType() == LayerType::Permute || base.GetType() == LayerType::Transpose);
        const TensorInfo& inputInfo = base.GetInputSlot(0).GetTensorInfo();
        const TensorInfo& intermediateInfo = base.GetOutputSlot(0).GetTensorInfo();
        if (intermediateInfo.GetNumDimensions() != 4)
        {
            // Must be 4D, otherwise the below checks do not make sense
            return;
        }
        if (!static_cast<PermuteType&>(base).GetParameters().m_DimMappings.IsEqual(PermutationVector{ 3, 1, 2, 0 }))
        {
            // Must swap batch and channels dimensions, otherwise it is not the (original) channels dimension
            // that is being decomposed.
            return;
        }
 
        // Validate child layer (the BatchToSpace) is compatible
        Layer& child = connection.GetOwningLayer();
        ARMNN_ASSERT(child.GetType() == LayerType::BatchToSpaceNd);
        const TensorInfo& outputInfo = child.GetOutputSlot(0).GetTensorInfo();
        const BatchToSpaceNdDescriptor& batchToSpaceDesc = static_cast<BatchToSpaceNdLayer&>(child).GetParameters();
        if (batchToSpaceDesc.m_DataLayout != DataLayout::NHWC)
        {
            // The rest of this function assumes NHWC, although in future this restriction could be lifted.
            return;
        }
        if (batchToSpaceDesc.m_Crops != std::vector<std::pair<unsigned int, unsigned int>>{ { 0, 0 }, { 0, 0 } })
        {
            // Cropping is not supported in DepthToSpace
            return;
        }
        if (batchToSpaceDesc.m_BlockShape.size() != 2 ||
        batchToSpaceDesc.m_BlockShape[0] != batchToSpaceDesc.m_BlockShape[1])
        {
            // Asymmetric or non-2D block sizes are not supported by DepthToSpace
            return;
        }
        uint32_t blockSize = batchToSpaceDesc.m_BlockShape[0];
        if (outputInfo.GetShape()[0] != 1 || outputInfo.GetShape()[3] != 1)
        {
            // The final output must have 1 batch and 1 channel because these dimensions will be swapped around
            // once we make the substitution, and it needs to be equivalent.
            return;
        }
 
        // Validate the intermediate tensor quantization params.
        // These must be identical to either the input or output quantization params, otherwise the intermediate tensor
        // may not have sufficient range/precision to preserve the values.
        // This would mean that once we perform the substitution this loss of precision will no longer occur,
        // so we would have changed the meaning of the network.
        bool isIntermediateQuantParamsSameAsInput =
                intermediateInfo.GetQuantizationScale() == inputInfo.GetQuantizationScale() &&
                intermediateInfo.GetQuantizationOffset() == inputInfo.GetQuantizationOffset();
        bool isIntermediateQuantParamsSameAsOutput =
                intermediateInfo.GetQuantizationScale() == outputInfo.GetQuantizationScale() &&
                intermediateInfo.GetQuantizationOffset() == outputInfo.GetQuantizationOffset();
        if (!isIntermediateQuantParamsSameAsInput && !isIntermediateQuantParamsSameAsOutput)
        {
            return;
        }
 
        // Insert equivalent DepthToSpace layer
        const std::string name = std::string("merged-") + base.GetName() + std::string("-with-") + child.GetName();
 
        // Inserts equivalent reshape before base layer.
        const DepthToSpaceDescriptor depthToSpaceDesc(blockSize, DataLayout::NHWC);
        auto& depthToSpace = *graph.InsertNewLayer<DepthToSpaceLayer>(base.GetInputSlot(0),
                                                                      depthToSpaceDesc,
                                                                      name.c_str());
 
        // Moves connections from child output to new layer.
        // Child layer will be removed as it's left unconnected.
        // Base layer will be removed if left unconnected.
        child.GetOutputSlot().MoveAllConnections(depthToSpace.GetOutputSlot());
    }

References ARMNN_ASSERT, armnn::BatchToSpaceNd, InputSlot::GetConnectedOutputSlot(), Layer::GetInputSlot(), TensorInfo::GetNumDimensions(), Layer::GetOutputSlot(), InputSlot::GetOwningLayer(), OutputSlot::GetOwningLayer(), InputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), Layer::GetType(), BatchToSpaceNdDescriptor::m_Crops, BatchToSpaceNdDescriptor::m_DataLayout, armnn::NHWC, armnn::Permute, and armnn::Transpose.

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The documentation for this class was generated from the following file:

• src/armnn/optimizations/PermuteAndBatchToSpaceAsDepthToSpace.hpp