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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "ConstantLayer.hpp"
#include <Layer.hpp>
namespace armnn
{
template <typename Parameters>
class LayerWithParameters : public Layer
{
public:
using DescriptorType = Parameters;
const Parameters& GetParameters() const override { return m_Param; }
/// Helper to serialize the layer parameters to string
/// (currently used in DotSerializer and company).
void SerializeLayerParameters(ParameterStringifyFunction& fn) const override
{
StringifyLayerParameters<Parameters>::Serialize(fn, m_Param);
Layer::SerializeLayerParameters(fn);
}
protected:
LayerWithParameters(unsigned int numInputSlots,
unsigned int numOutputSlots,
LayerType type,
const Parameters& param,
const char* name)
: Layer(numInputSlots, numOutputSlots, type, name)
, m_Param(param)
{
}
~LayerWithParameters() = default;
/// Helper function to reduce duplication in *Layer::CreateWorkload.
template <typename QueueDescriptor>
WorkloadInfo PrepInfoAndDesc(QueueDescriptor& descriptor) const
{
descriptor.m_Parameters = m_Param;
descriptor.m_AllowExpandedDims = GetAllowExpandedDims();
return Layer::PrepInfoAndDesc(descriptor);
}
/// The parameters for the layer (not including tensor-valued weights etc.).
Parameters m_Param;
void ExecuteStrategy(IStrategy& strategy) const override
{
strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
}
Layer::ImmutableConstantTensors GetConnectedConstantAsInputTensors() const
{
Layer::ImmutableConstantTensors tensors;
for (unsigned int i = 0; i < GetNumInputSlots(); ++i)
{
if (GetInputSlot(i).GetConnection() && GetInputSlot(i).GetTensorInfo().IsConstant())
{
auto &inputLayer = GetInputSlot(i).GetConnectedOutputSlot()->GetOwningLayer();
if (inputLayer.GetType() == armnn::LayerType::Constant)
{
auto &constantLayer = static_cast<ConstantLayer&>(inputLayer);
tensors.push_back(constantLayer.m_LayerOutput);
}
}
}
return tensors;
}
};
} // namespace
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