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//
// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "Optimization.hpp"
#include "NetworkUtils.hpp"
#include <armnnUtils/Permute.hpp>
#include <fmt/format.h>
namespace armnn
{
namespace optimizations
{
class PermuteDepthwiseConv2dWeightsImpl
{
public:
void Run(Graph& graph, Layer& layer) const
{
if (layer.GetType() == LayerType::DepthwiseConvolution2d)
{
AddPermuteLayer(graph, PolymorphicDowncast<DepthwiseConvolution2dLayer*>(&layer));
}
}
protected:
PermuteDepthwiseConv2dWeightsImpl() = default;
~PermuteDepthwiseConv2dWeightsImpl() = default;
private:
/// ArmNN format for weights for depthwise is [1, H, W, C] independently of the input/output layout
///
/// ACL format for weights for depthwise is:
/// - [1, H, W, C] for [N, H, W, C] input/output layout (matches with ArmNN)
/// - [1, C, H, W] for [N, C, H, W] input/output layout
///
/// Therefore ArmNN weights have to be permuted when input/output layout is [N, C, H, W] to pass them to ACL.
static void AddPermuteLayer(Graph& graph, DepthwiseConvolution2dLayer* layer)
{
TensorInfo inputInfo = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo();
TensorInfo weightInfo = layer->GetInputSlot(1).GetConnectedOutputSlot()->GetTensorInfo();
if (layer->GetParameters().m_DataLayout == armnn::DataLayout::NHWC)
{
// No permutation required. Input and weights data layouts are the same.
return;
}
else if (layer->GetParameters().m_DataLayout == armnn::DataLayout::NCHW)
{
// Weights permutation required. Weights [N,H,W,C] and input [N,C,H,W] data layouts are different.
// [ 1, H, W, I*M] --> [ 1, I * M, H, W ]
PermutationVector permutationVector = { 0, 2, 3, 1 };
TensorInfo weightsPermuted = armnnUtils::Permuted(weightInfo, permutationVector);
// Inserts NewLayer so layers don't need to be re-sorted.
PermuteLayer* permuteLayer =
graph.InsertNewLayer<PermuteLayer>(layer->GetInputSlot(1),
PermuteDescriptor(permutationVector),
"permute_layer");
permuteLayer->GetOutputSlot().SetTensorInfo(weightsPermuted);
// Assign Permute BackendId to be the same as the Depthwise Conv2d BackendId.
// Needed as backends have already been assigned at this stage.
permuteLayer->SetBackendId(layer->GetBackendId());
}
else
{
throw InvalidArgumentException(fmt::format("Unknown data layout for tensor info conversion: {}",
GetDataLayoutName(layer->GetParameters().m_DataLayout)));
}
}
};
using PermuteDepthwiseConv2dWeights = OptimizeForType<Layer, PermuteDepthwiseConv2dWeightsImpl>;
} // namespace optimizations
} // namespace armnn
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