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//
// Copyright © 2019 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "NeonArgMinMaxWorkload.hpp"
#include "NeonWorkloadUtils.hpp"
#include <aclCommon/ArmComputeTensorUtils.hpp>
#include <armnn/backends/TensorHandle.hpp>
#include <armnn/utility/NumericCast.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
#include <armnnUtils/TensorUtils.hpp>
#include <arm_compute/runtime/NEON/functions/NEArgMinMaxLayer.h>
namespace
{
unsigned int CalcAclAxis(unsigned int numDimensions, unsigned int axisIndex)
{
return (numDimensions - axisIndex) - 1;
}
} //namespace
namespace armnn
{
arm_compute::Status NeonArgMinMaxWorkloadValidate(const TensorInfo& input,
const TensorInfo& output,
const ArgMinMaxDescriptor& descriptor)
{
const arm_compute::TensorInfo aclInput = armcomputetensorutils::BuildArmComputeTensorInfo(input);
const arm_compute::TensorInfo aclOutput = armcomputetensorutils::BuildArmComputeTensorInfo(output);
auto numDims = input.GetNumDimensions();
auto unsignedAxis = armnnUtils::GetUnsignedAxis(numDims, descriptor.m_Axis);
int aclAxis = armnn::numeric_cast<int>(CalcAclAxis(numDims, unsignedAxis));
if (descriptor.m_Function == ArgMinMaxFunction::Max)
{
return arm_compute::NEArgMinMaxLayer::validate(&aclInput, aclAxis, &aclOutput,
arm_compute::ReductionOperation::ARG_IDX_MAX);
}
else
{
return arm_compute::NEArgMinMaxLayer::validate(&aclInput, aclAxis, &aclOutput,
arm_compute::ReductionOperation::ARG_IDX_MIN);
}
}
NeonArgMinMaxWorkload::NeonArgMinMaxWorkload(const ArgMinMaxQueueDescriptor& descriptor,
const WorkloadInfo& info)
: NeonBaseWorkload<ArgMinMaxQueueDescriptor>(descriptor, info)
{
// Report Profiling Details
ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonArgMinMaxWorkload_Construct",
descriptor.m_Parameters,
info,
this->GetGuid());
arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
auto numDims = info.m_InputTensorInfos[0].GetNumDimensions();
auto unsignedAxis = armnnUtils::GetUnsignedAxis(numDims, m_Data.m_Parameters.m_Axis);
int aclAxis = armnn::numeric_cast<int>(CalcAclAxis(numDims, unsignedAxis));
auto layer = std::make_unique<arm_compute::NEArgMinMaxLayer>();
if (m_Data.m_Parameters.m_Function == ArgMinMaxFunction::Max)
{
layer->configure(&input, aclAxis, &output, arm_compute::ReductionOperation::ARG_IDX_MAX);
}
else
{
layer->configure(&input, aclAxis, &output, arm_compute::ReductionOperation::ARG_IDX_MIN);
}
m_ArgMinMaxLayer.reset(layer.release());
}
void NeonArgMinMaxWorkload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonArgMinMaxWorkload_Execute", this->GetGuid());
m_ArgMinMaxLayer->run();
}
} //namespace armnn
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