NeonReduceWorkload.cpp

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//
// Copyright © 2021-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
 
#include "NeonReduceWorkload.hpp"
 
#include <aclCommon/ArmComputeUtils.hpp>
#include <aclCommon/ArmComputeTensorUtils.hpp>
 
#include <neon/NeonTensorHandle.hpp>
 
#include "NeonWorkloadUtils.hpp"
 
namespace armnn
{
using namespace armcomputetensorutils;
 
arm_compute::Status NeonReduceWorkloadValidate(const TensorInfo& input,
                                               const TensorInfo& output,
                                               const ReduceDescriptor& descriptor)
{
    if ( descriptor.m_vAxis.size()==1 || descriptor.m_vAxis.empty())
    {
        const arm_compute::TensorInfo aclInputInfo  = armcomputetensorutils::BuildArmComputeTensorInfo(input);
        const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output);
 
        arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(aclInputInfo.num_dimensions(),
                                                                              input.GetNumDimensions(),
                                                                              descriptor.m_vAxis);
 
        return arm_compute::NEReductionOperation::validate(&aclInputInfo,
                                                           &aclOutputInfo,
                                                           static_cast<unsigned int>(coords[0]),
                                                           ConvertReductionOperationToAcl(descriptor),
                                                           descriptor.m_KeepDims);
    }
    else
    {
        // Validate layer if there are multiple axes.
        arm_compute::Status status;
        IsMultiAxesReduceSupported(NeonReduceWorkloadValidate, input, output, descriptor, status);
        return status;
    }
}
 
NeonReduceWorkload::NeonReduceWorkload(const ReduceQueueDescriptor& descriptor, const WorkloadInfo& info)
    : NeonBaseWorkload<ReduceQueueDescriptor>(descriptor, info)
{
    // Report Profiling Details
    ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonReduceWorkload_Construct",
                                         descriptor.m_Parameters,
                                         info,
                                         this->GetGuid());
 
    m_Data.ValidateInputsOutputs("NeonReduceWorkload", 1, 1);
 
    arm_compute::ITensor& input  = static_cast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
    arm_compute::ITensor& output = static_cast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
 
    arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(input.info()->num_dimensions(),
                                                                          info.m_InputTensorInfos[0].GetNumDimensions(),
                                                                          m_Data.m_Parameters.m_vAxis);
 
    m_Layer.configure(&input,
                      &output,
                      static_cast<unsigned int>(coords[0]),
                      ConvertReductionOperationToAcl(m_Data.m_Parameters),
                      m_Data.m_Parameters.m_KeepDims);
}
 
void NeonReduceWorkload::Execute() const
{
    ARMNN_SCOPED_PROFILING_EVENT_NEON_NAME_GUID("NeonReduceWorkload_Execute");
    m_Layer.run();
}
 
} //namespace armnn