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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "RefElementwiseWorkload.hpp"
#include "ElementwiseFunction.hpp"
#include "RefWorkloadUtils.hpp"
#include "Profiling.hpp"
#include "StringMapping.hpp"
#include "TypeUtils.hpp"
#include <vector>
namespace armnn
{
template <typename Functor,
typename armnn::DataType DataType,
typename ParentDescriptor,
typename armnn::StringMapping::Id DebugString>
void RefElementwiseWorkload<Functor, DataType, ParentDescriptor, DebugString>::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, StringMapping::Instance().Get(DebugString));
const TensorInfo& inputInfo0 = GetTensorInfo(m_Data.m_Inputs[0]);
const TensorInfo& inputInfo1 = GetTensorInfo(m_Data.m_Inputs[1]);
const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]);
const TensorShape& inShape0 = inputInfo0.GetShape();
const TensorShape& inShape1 = inputInfo1.GetShape();
const TensorShape& outShape = outputInfo.GetShape();
switch(DataType)
{
case armnn::DataType::QuantisedAsymm8:
{
std::vector<float> results(outputInfo.GetNumElements());
ElementwiseFunction<Functor, float, float>(inShape0,
inShape1,
outShape,
Dequantize(GetInputTensorDataU8(0, m_Data), inputInfo0).data(),
Dequantize(GetInputTensorDataU8(1, m_Data), inputInfo1).data(),
results.data());
Quantize(GetOutputTensorDataU8(0, m_Data), results.data(), outputInfo);
break;
}
case armnn::DataType::Float32:
{
ElementwiseFunction<Functor, float, float>(inShape0,
inShape1,
outShape,
GetInputTensorDataFloat(0, m_Data),
GetInputTensorDataFloat(1, m_Data),
GetOutputTensorDataFloat(0, m_Data));
break;
}
default:
BOOST_ASSERT_MSG(false, "Unknown Data Type!");
break;
}
}
}
template class armnn::RefElementwiseWorkload<std::plus<float>,
armnn::DataType::Float32,
armnn::AdditionQueueDescriptor,
armnn::StringMapping::RefAdditionWorkload_Execute>;
template class armnn::RefElementwiseWorkload<std::plus<float>,
armnn::DataType::QuantisedAsymm8,
armnn::AdditionQueueDescriptor,
armnn::StringMapping::RefAdditionWorkload_Execute>;
template class armnn::RefElementwiseWorkload<std::minus<float>,
armnn::DataType::Float32,
armnn::SubtractionQueueDescriptor,
armnn::StringMapping::RefSubtractionWorkload_Execute>;
template class armnn::RefElementwiseWorkload<std::minus<float>,
armnn::DataType::QuantisedAsymm8,
armnn::SubtractionQueueDescriptor,
armnn::StringMapping::RefSubtractionWorkload_Execute>;
template class armnn::RefElementwiseWorkload<std::multiplies<float>,
armnn::DataType::Float32,
armnn::MultiplicationQueueDescriptor,
armnn::StringMapping::RefMultiplicationWorkload_Execute>;
template class armnn::RefElementwiseWorkload<std::multiplies<float>,
armnn::DataType::QuantisedAsymm8,
armnn::MultiplicationQueueDescriptor,
armnn::StringMapping::RefMultiplicationWorkload_Execute>;
template class armnn::RefElementwiseWorkload<std::divides<float>,
armnn::DataType::Float32,
armnn::DivisionQueueDescriptor,
armnn::StringMapping::RefDivisionWorkload_Execute>;
template class armnn::RefElementwiseWorkload<std::divides<float>,
armnn::DataType::QuantisedAsymm8,
armnn::DivisionQueueDescriptor,
armnn::StringMapping::RefDivisionWorkload_Execute>;
template class armnn::RefElementwiseWorkload<armnn::maximum<float>,
armnn::DataType::Float32,
armnn::MaximumQueueDescriptor,
armnn::StringMapping::RefMaximumWorkload_Execute>;
template class armnn::RefElementwiseWorkload<armnn::maximum<float>,
armnn::DataType::QuantisedAsymm8,
armnn::MaximumQueueDescriptor,
armnn::StringMapping::RefMaximumWorkload_Execute>;
template class armnn::RefElementwiseWorkload<armnn::minimum<float>,
armnn::DataType::Float32,
armnn::MinimumQueueDescriptor,
armnn::StringMapping::RefMinimumWorkload_Execute>;
template class armnn::RefElementwiseWorkload<armnn::minimum<float>,
armnn::DataType::QuantisedAsymm8,
armnn::MinimumQueueDescriptor,
armnn::StringMapping::RefMinimumWorkload_Execute>;
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