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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "NeonConstantWorkload.hpp"
#include <arm_compute/core/Types.h>
#include <armnnUtils/Half.hpp>
#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
#include <backends/neon/NeonTensorHandle.hpp>
#include <backends/CpuTensorHandle.hpp>
#include <backends/Workload.hpp>
#include <boost/cast.hpp>
namespace armnn
{
NeonConstantWorkload::NeonConstantWorkload(const ConstantQueueDescriptor& descriptor,
const WorkloadInfo& info)
: BaseWorkload<ConstantQueueDescriptor>(descriptor, info)
, m_RanOnce(false)
{
}
void NeonConstantWorkload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonConstantWorkload_Execute");
using namespace armcomputetensorutils;
// The intermediate tensor held by the corresponding layer output handler can be initialised with the
// given data on the first inference, then reused for subsequent inferences.
// The initialisation cannot happen at workload construction time since the ACL kernel for the next layer
// may not have been configured at the time.
if (!m_RanOnce)
{
const ConstantQueueDescriptor& data = this->m_Data;
BOOST_ASSERT(data.m_LayerOutput != nullptr);
arm_compute::ITensor& output =
boost::polymorphic_downcast<NeonTensorHandle*>(data.m_Outputs[0])->GetTensor();
arm_compute::DataType computeDataType =
boost::polymorphic_downcast<NeonTensorHandle*>(data.m_Outputs[0])->GetDataType();
switch (computeDataType)
{
case arm_compute::DataType::F16:
{
CopyArmComputeITensorData(data.m_LayerOutput->GetConstTensor<Half>(), output);
break;
}
case arm_compute::DataType::F32:
{
CopyArmComputeITensorData(data.m_LayerOutput->GetConstTensor<float>(), output);
break;
}
case arm_compute::DataType::QASYMM8:
{
CopyArmComputeITensorData(data.m_LayerOutput->GetConstTensor<uint8_t>(), output);
break;
}
default:
{
BOOST_ASSERT_MSG(false, "Unknown data type");
break;
}
}
m_RanOnce = true;
}
}
} //namespace armnn
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