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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "NeonL2NormalizationFloatWorkload.hpp"
#include <backends/aclCommon/ArmComputeUtils.hpp>
namespace armnn
{
using namespace armcomputetensorutils;
arm_compute::Status NeonL2NormalizationWorkloadValidate(const TensorInfo& input,
const TensorInfo& output,
const L2NormalizationDescriptor& descriptor)
{
const arm_compute::TensorInfo aclInput = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
const arm_compute::TensorInfo aclOutput = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout);
arm_compute::NormalizationLayerInfo normalizationInfo =
CreateAclNormalizationLayerInfoForL2Normalization(input, descriptor.m_DataLayout);
return arm_compute::NENormalizationLayer::validate(&aclInput, &aclOutput, normalizationInfo);
}
NeonL2NormalizationFloatWorkload::NeonL2NormalizationFloatWorkload(const L2NormalizationQueueDescriptor& descriptor,
const WorkloadInfo& info, std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
: FloatWorkload<L2NormalizationQueueDescriptor>(descriptor, info)
, m_Layer(memoryManager)
{
m_Data.ValidateInputsOutputs("NeonL2NormalizationFloatWorkload", 1, 1);
arm_compute::ITensor& input = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
arm_compute::ITensor& output = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
input.info()->set_data_layout(aclDataLayout);
output.info()->set_data_layout(aclDataLayout);
m_Layer.configure(&input, &output,
CreateAclNormalizationLayerInfoForL2Normalization(info.m_InputTensorInfos[0],
m_Data.m_Parameters.m_DataLayout));
}
void NeonL2NormalizationFloatWorkload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonL2NormalizationFloatWorkload_Execute");
m_Layer.run();
}
} //namespace armnn
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