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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// See LICENSE file in the project root for full license information.
//
#include "NeonL2NormalizationFloat32Workload.hpp"
#include "backends/ArmComputeUtils.hpp"
namespace armnn
{
arm_compute::Status NeonL2NormalizationWorkloadValidate(const TensorInfo& input,
const TensorInfo& output)
{
const arm_compute::TensorInfo aclInput = armcomputetensorutils::BuildArmComputeTensorInfo(input);
const arm_compute::TensorInfo aclOutput = armcomputetensorutils::BuildArmComputeTensorInfo(output);
arm_compute::NormalizationLayerInfo normalizationInfo =
CreateAclNormalizationLayerInfoForL2Normalization(input);
return arm_compute::NENormalizationLayer::validate(&aclInput, &aclOutput, normalizationInfo);
}
NeonL2NormalizationFloat32Workload::NeonL2NormalizationFloat32Workload(const L2NormalizationQueueDescriptor& descriptor,
const WorkloadInfo& info, std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
: FloatWorkload<L2NormalizationQueueDescriptor>(descriptor, info)
, m_Layer(memoryManager)
{
m_Data.ValidateInputsOutputs("NeonL2NormalizationFloat32Workload", 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();
m_Layer.configure(&input, &output, CreateAclNormalizationLayerInfoForL2Normalization(info.m_InputTensorInfos[0]));
}
void NeonL2NormalizationFloat32Workload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonL2NormalizationFloat32Workload_Execute");
m_Layer.run();
}
} //namespace armnn
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