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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "RefQuantizeWorkload.hpp"
#include "RefWorkloadUtils.hpp"
#include <armnn/TypesUtils.hpp>
namespace armnn
{
namespace
{
void QuantizeImpl(Decoder<float>& in, Encoder<float>& out, size_t numValues)
{
for (unsigned int i = 0; i < numValues; i++)
{
in[i];
out[i];
out.Set(in.Get());
}
}
} //namespace
RefQuantizeWorkload::RefQuantizeWorkload(const QuantizeQueueDescriptor& descriptor, const WorkloadInfo &info)
: BaseWorkload(descriptor, info)
, m_NumElements(info.m_InputTensorInfos[0].GetNumElements())
{
}
void RefQuantizeWorkload::Execute() const
{
Execute(m_Data.m_Inputs, m_Data.m_Outputs);
}
void RefQuantizeWorkload::ExecuteAsync(WorkingMemDescriptor &workingMemDescriptor)
{
Execute(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
}
void RefQuantizeWorkload::Execute(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const
{
std::unique_ptr<Decoder<float>> inputDecoder = MakeDecoder<float>(GetTensorInfo(inputs[0]), inputs[0]->Map());
std::unique_ptr<Encoder<float>> outputEncoder = MakeEncoder<float>(GetTensorInfo(outputs[0]), outputs[0]->Map());
QuantizeImpl(*inputDecoder, *outputEncoder, m_NumElements);
}
} //namespace armnn
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