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//
// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ClReduceWorkload.hpp"
#include <cl/ClTensorHandle.hpp>
#include <aclCommon/ArmComputeUtils.hpp>
#include <aclCommon/ArmComputeTensorUtils.hpp>
#include "ClWorkloadUtils.hpp"
namespace armnn
{
using namespace armcomputetensorutils;
arm_compute::Status ClReduceWorkloadValidate(const TensorInfo& input,
const TensorInfo& output,
const ReduceDescriptor& desc)
{
const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input);
arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(aclInputInfo.num_dimensions(),
input.GetNumDimensions(),
desc.m_vAxis);
// As ACL only support one axis, validate the layer for each axis if more than one is present.
if (!desc.m_vAxis.empty() && desc.m_vAxis.size() > 1)
{
arm_compute::Status status;
for (unsigned int i = 0; i != desc.m_vAxis.size(); ++i)
{
TensorInfo inputToModify = input;
std::vector<uint32_t> singleAxis(1, desc.m_vAxis[i]);
// Calculate the output shape using the input shape for a single axis.
// Currently the output TensorInfo inferred will be reduced upon multiple axis
// which will fail validation as only one axis is supported.
const TensorShape& reducedShape = ComputeReductionTensorShape(inputToModify, singleAxis, desc.m_KeepDims);
inputToModify.SetShape(reducedShape);
const arm_compute::TensorInfo aclOutputInfoModified =
armcomputetensorutils::BuildArmComputeTensorInfo(inputToModify);
status = arm_compute::CLReductionOperation::validate(&aclInputInfo,
&aclOutputInfoModified,
static_cast<unsigned int>(coords[i]),
ConvertReductionOperationToAcl(desc),
desc.m_KeepDims);
if (!status)
{
break;
}
}
return status;
}
else
{
const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output);
return arm_compute::CLReductionOperation::validate(&aclInputInfo,
&aclOutputInfo,
static_cast<unsigned int>(coords[0]),
ConvertReductionOperationToAcl(desc),
desc.m_KeepDims);
}
}
ClReduceWorkload::ClReduceWorkload(const ReduceQueueDescriptor& descriptor, const WorkloadInfo& info)
: BaseWorkload<ReduceQueueDescriptor>(descriptor, info)
{
m_Data.ValidateInputsOutputs("ClReduceWorkload", 1, 1);
arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(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 ClReduceWorkload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_CL("ClReduceWorkload_Execute");
m_Layer.run();
}
} //namespace armnn
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