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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ClAdditionWorkload.hpp"
#include <backends/cl/ClTensorHandle.hpp>
#include <backends/CpuTensorHandle.hpp>
#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
#include "ClWorkloadUtils.hpp"
namespace armnn
{
using namespace armcomputetensorutils;
static constexpr arm_compute::ConvertPolicy g_AclConvertPolicy = arm_compute::ConvertPolicy::SATURATE;
template <armnn::DataType... T>
ClAdditionWorkload<T...>::ClAdditionWorkload(const AdditionQueueDescriptor& descriptor,
const WorkloadInfo& info)
: TypedWorkload<AdditionQueueDescriptor, T...>(descriptor, info)
{
this->m_Data.ValidateInputsOutputs("ClAdditionWorkload", 2, 1);
arm_compute::ICLTensor& input0 = static_cast<IClTensorHandle*>(this->m_Data.m_Inputs[0])->GetTensor();
arm_compute::ICLTensor& input1 = static_cast<IClTensorHandle*>(this->m_Data.m_Inputs[1])->GetTensor();
arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(this->m_Data.m_Outputs[0])->GetTensor();
m_Layer.configure(&input0, &input1, &output, g_AclConvertPolicy);
}
template <armnn::DataType... T>
void ClAdditionWorkload<T...>::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_CL("ClAdditionWorkload_Execute");
m_Layer.run();
}
bool ClAdditionValidate(const TensorInfo& input0,
const TensorInfo& input1,
const TensorInfo& output,
std::string* reasonIfUnsupported)
{
const arm_compute::TensorInfo aclInput0Info = BuildArmComputeTensorInfo(input0);
const arm_compute::TensorInfo aclInput1Info = BuildArmComputeTensorInfo(input1);
const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output);
const arm_compute::Status aclStatus = arm_compute::CLArithmeticAddition::validate(&aclInput0Info,
&aclInput1Info,
&aclOutputInfo,
g_AclConvertPolicy);
const bool supported = (aclStatus.error_code() == arm_compute::ErrorCode::OK);
if (!supported && reasonIfUnsupported)
{
*reasonIfUnsupported = aclStatus.error_description();
}
return supported;
}
} //namespace armnn
template class armnn::ClAdditionWorkload<armnn::DataType::Float16, armnn::DataType::Float32>;
template class armnn::ClAdditionWorkload<armnn::DataType::QuantisedAsymm8>;
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