src/backends/neon/workloads/NeonConvertFp32ToFp16Workload.cpp

//
// Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//

#include "NeonConvertFp32ToFp16Workload.hpp"

#include <arm_compute/runtime/NEON/functions/NECast.h>
#include <Half.hpp>
#include <Profiling.hpp>

#include <armnnUtils/FloatingPointConverter.hpp>

#include <backendsCommon/WorkloadUtils.hpp>

static constexpr arm_compute::ConvertPolicy g_AclConvertPolicy = arm_compute::ConvertPolicy::SATURATE;

namespace armnn
{

arm_compute::Status NeonConvertFp32ToFp16WorkloadValidate(const TensorInfo& input, const TensorInfo& output)
{
    // Fallback to portable software implementation if Compute Library NECast won't work, so
    // this method always returns success

    armnn::IgnoreUnused(input);
    armnn::IgnoreUnused(output);
    return arm_compute::Status();
}

NeonConvertFp32ToFp16Workload::NeonConvertFp32ToFp16Workload(const ConvertFp32ToFp16QueueDescriptor& descriptor,
                                                             const WorkloadInfo& info)
    : Float32ToFloat16Workload<ConvertFp32ToFp16QueueDescriptor>(descriptor, info)
{
    this->m_Data.ValidateInputsOutputs("NeonConvertFp32ToFp16Workload", 1, 1);

    arm_compute::ITensor& input  = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
    arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();

    if (arm_compute::NECast::validate(input.info(), output.info(), g_AclConvertPolicy))
    {
        // Use NECast if supported (needs hardware support for FP16)
        m_Cast.reset(new arm_compute::NECast);
        m_Cast->configure(&input, &output, g_AclConvertPolicy);
    }
    else
    {
        // Else use software implementation from Half.hpp
        GatherTensorHandlePairs(descriptor, m_TensorHandlePairs);
    }
}

void NeonConvertFp32ToFp16Workload::Execute() const
{
    ARMNN_SCOPED_PROFILING_EVENT_NEON_NAME_GUID("NeonConvertFp32ToFp16Workload_Execute");

    if (m_Cast)
    {
        // Use NECast if supported and initialised
        m_Cast->run();
    }
    else
    {
        // Else use softwre implementabion using Half.hpp
        auto convertFunc = [](uint8_t* dst, const uint8_t* src, size_t size)
            {
                auto input = reinterpret_cast<const float*>(src);
                auto output = reinterpret_cast<Half*>(dst);
                size_t numElements = size/2; // 2 bytes per fp16
                armnnUtils::FloatingPointConverter::ConvertFloat32To16(input, numElements, output);
            };

        for (const auto& pair : m_TensorHandlePairs)
        {
            CopyTensorContentsGeneric(pair.first, pair.second, convertFunc);
        }
    }
}

void NeonConvertFp32ToFp16Workload::ReplaceInputTensorHandle(ITensorHandle* tensorHandle, unsigned int slot)
{
    ITensorHandle* backupHandle = this->m_Data.m_Inputs[slot];
    this->m_Data.m_Inputs[slot] = tensorHandle;
    try
    {
        Reconfigure();
    }
    catch(armnn::UnimplementedException& e)
    {
        // Cannot reconfigure, revert the slot back and throw the exception.
        this->m_Data.m_Inputs[slot] = backupHandle;
        throw e;
    }
}

// Replace output tensor handle with the given TensorHandle
void NeonConvertFp32ToFp16Workload::ReplaceOutputTensorHandle(ITensorHandle* tensorHandle, unsigned int slot)
{
    ITensorHandle* backupHandle = this->m_Data.m_Inputs[slot];
    this->m_Data.m_Inputs[slot] = tensorHandle;
    try
    {
        Reconfigure();
    }
    catch(armnn::UnimplementedException& e)
    {
        // Cannot reconfigure, revert the slot back and throw the exception.
        this->m_Data.m_Inputs[slot] = backupHandle;
        throw e;
    }
}

void NeonConvertFp32ToFp16Workload::Reconfigure()
{
    throw armnn::UnimplementedException("Reconfigure not implemented for this workload");
}

} //namespace armnn