src/armnn/optimizations/PermuteAndBatchToSpaceAsDepthToSpace.hpp

//
// Copyright © 2019 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once

#include "Optimization.hpp"

namespace armnn
{
namespace optimizations
{

/// 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.
template <typename PermuteType>
class PermuteAndBatchToSpaceAsDepthToSpaceImpl
{
public:
    void Run(Graph& graph, InputSlot& connection) const
    {
        // Validate base layer (the Permute) is compatible
        Layer& base = connection.GetConnectedOutputSlot()->GetOwningLayer();
        BOOST_ASSERT(base.GetType() == LayerType::Permute || base.GetType() == LayerType::Transpose);
        const TensorInfo& inputInfo = base.GetInputSlot(0).GetConnection()->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();
        BOOST_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());
        depthToSpace.GetOutputHandler().SetTensorInfo(outputInfo);

        // 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());
    }
};

using PermuteAndBatchToSpaceAsDepthToSpace = OptimizeForConnection<PermuteLayer, BatchToSpaceNdLayer,
    PermuteAndBatchToSpaceAsDepthToSpaceImpl<PermuteLayer>>;
using TransposeAndBatchToSpaceAsDepthToSpace = OptimizeForConnection<TransposeLayer, BatchToSpaceNdLayer,
    PermuteAndBatchToSpaceAsDepthToSpaceImpl<TransposeLayer>>;
}    // namespace optimizations
}    // namespace armnn