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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "NeonMultiplicationWorkload.hpp"
#include "NeonWorkloadUtils.hpp"
#include <aclCommon/ArmComputeUtils.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
#include <arm_compute/runtime/NEON/functions/NEPixelWiseMultiplication.h>
namespace armnn
{
arm_compute::Status NeonMultiplicationWorkloadValidate(const TensorInfo& input0,
const TensorInfo& input1,
const TensorInfo& output,
const ActivationDescriptor* activationDescriptor)
{
const arm_compute::TensorInfo aclInput1 = armcomputetensorutils::BuildArmComputeTensorInfo(input0);
const arm_compute::TensorInfo aclInput2 = armcomputetensorutils::BuildArmComputeTensorInfo(input1);
const arm_compute::TensorInfo aclOutput = armcomputetensorutils::BuildArmComputeTensorInfo(output);
auto convertPolicy = (IsQuantizedType(input0.GetDataType()) || IsQuantizedType(input1.GetDataType())) ?
arm_compute::ConvertPolicy::SATURATE :
arm_compute::ConvertPolicy::WRAP;
const arm_compute::ActivationLayerInfo activationInfo = ConvertActivationDescriptorToAclActivationLayerInfo(
activationDescriptor);
// At the time of writing, configure() will fail if a rounding policy other than TO_ZERO is supplied to it,
// when providing a scale of 1.0 for F32 tensors, even though the provided rounding policy appears to be
// ignored for F32 tensors.
return arm_compute::NEPixelWiseMultiplication::validate(&aclInput1,
&aclInput2,
&aclOutput,
1.0f,
convertPolicy,
arm_compute::RoundingPolicy::TO_ZERO,
activationInfo);
}
NeonMultiplicationWorkload::NeonMultiplicationWorkload(const MultiplicationQueueDescriptor& descriptor,
const WorkloadInfo& info)
: BaseWorkload<MultiplicationQueueDescriptor>(descriptor, info)
{
m_Data.ValidateInputsOutputs("NeonMultiplicationWorkload", 2, 1);
arm_compute::ITensor& input1 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
arm_compute::ITensor& input2 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor();
arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
auto convertPolicy = (IsQuantizedType(info.m_InputTensorInfos[0].GetDataType()) ||
IsQuantizedType(info.m_InputTensorInfos[1].GetDataType())) ?
arm_compute::ConvertPolicy::SATURATE :
arm_compute::ConvertPolicy::WRAP;
const arm_compute::ActivationLayerInfo activationInfo = ConvertAdditionalInfoToAclActivationLayerInfo(descriptor);
// At the time of writing, configure() will fail if a rounding policy other than TO_ZERO is supplied to it,
// when providing a scale of 1.0 for F32 tensors, even though the provided rounding policy appears to be
// ignored for F32 tensors.
auto layer = std::make_unique<arm_compute::NEPixelWiseMultiplication>();
layer->configure(&input1,
&input2,
&output,
1.0f,
convertPolicy,
arm_compute::RoundingPolicy::TO_ZERO,
activationInfo);
m_PixelWiseMultiplication.reset(layer.release());
}
void NeonMultiplicationWorkload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonMultiplicationWorkload_Execute", this->GetGuid());
m_PixelWiseMultiplication->run();
}
} //namespace armnn
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