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//
// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "RefFakeQuantizationFloat32Workload.hpp"
#include "RefWorkloadUtils.hpp"
#include "Profiling.hpp"
#include <armnn/utility/NumericCast.hpp>
namespace armnn
{
void FakeQuantization(const float* inputData, float* outputData, uint32_t numElements, float min, float max)
{
float scale = (max - min) / 255.f;
int32_t offset = armnn::numeric_cast<int32_t>((-min * 255.f) / (max - min));
for (uint32_t i = 0; i < numElements; i++)
{
outputData[i] = static_cast<float>(armnn::Quantize<uint8_t>(inputData[i], scale, offset));
}
}
void RefFakeQuantizationFloat32Workload::Execute() const
{
Execute(m_Data.m_Inputs, m_Data.m_Outputs);
}
void RefFakeQuantizationFloat32Workload::ExecuteAsync(ExecutionData& executionData)
{
WorkingMemDescriptor* workingMemDescriptor = static_cast<WorkingMemDescriptor*>(executionData.m_Data);
Execute(workingMemDescriptor->m_Inputs, workingMemDescriptor->m_Outputs);
}
void RefFakeQuantizationFloat32Workload::Execute(std::vector<ITensorHandle*> inputs,
std::vector<ITensorHandle*> outputs) const
{
ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefFakeQuantizationFloat32Workload_Execute");
const TensorInfo& inputInfo = GetTensorInfo(inputs[0]);
const float* inputData = reinterpret_cast<const float*>(inputs[0]->Map());
float* outputData = reinterpret_cast<float*>(outputs[0]->Map());
FakeQuantization(inputData, outputData, inputInfo.GetNumElements(),
m_Data.m_Parameters.m_Min,
m_Data.m_Parameters.m_Max);
}
} //namespace armnn
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