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//
// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "NeonConstantWorkload.hpp"
#include <arm_compute/core/Types.h>
#include <BFloat16.hpp>
#include <Half.hpp>
#include <aclCommon/ArmComputeTensorUtils.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
#include <neon/NeonTensorHandle.hpp>
#include <armnn/backends/TensorHandle.hpp>
#include "NeonBaseWorkload.hpp"
namespace armnn
{
arm_compute::Status NeonConstantWorkloadValidate(const TensorInfo& output)
{
const arm_compute::TensorInfo neonOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output);
std::array<arm_compute::DataType,9> supportedTypes = {
arm_compute::DataType::BFLOAT16,
arm_compute::DataType::F16,
arm_compute::DataType::F32,
arm_compute::DataType::QASYMM8,
arm_compute::DataType::QASYMM8_SIGNED,
arm_compute::DataType::QSYMM16,
arm_compute::DataType::QSYMM8,
arm_compute::DataType::QSYMM8_PER_CHANNEL,
arm_compute::DataType::S32
};
auto it = std::find(begin(supportedTypes), end(supportedTypes), neonOutputInfo.data_type());
if (it != end(supportedTypes))
{
return arm_compute::Status{};
}
else
{
return arm_compute::Status{arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported DataType"};
}
}
NeonConstantWorkload::NeonConstantWorkload(const ConstantQueueDescriptor& descriptor,
const WorkloadInfo& info)
: NeonBaseWorkload<ConstantQueueDescriptor>(descriptor, info)
, m_RanOnce(false)
{
}
void NeonConstantWorkload::Execute() const
{
ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonConstantWorkload_Execute", this->GetGuid());
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;
ARMNN_ASSERT(data.m_LayerOutput != nullptr);
arm_compute::ITensor& output =
PolymorphicDowncast<NeonTensorHandle*>(data.m_Outputs[0])->GetTensor();
arm_compute::DataType computeDataType =
PolymorphicDowncast<NeonTensorHandle*>(data.m_Outputs[0])->GetDataType();
switch (computeDataType)
{
case arm_compute::DataType::BFLOAT16:
{
CopyArmComputeITensorData(data.m_LayerOutput->GetConstTensor<BFloat16>(), output);
break;
}
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;
}
case arm_compute::DataType::QASYMM8_SIGNED:
{
CopyArmComputeITensorData(data.m_LayerOutput->GetConstTensor<int8_t>(), output);
break;
}
case arm_compute::DataType::QSYMM16:
{
CopyArmComputeITensorData(data.m_LayerOutput->GetConstTensor<int16_t>(), output);
break;
}
case arm_compute::DataType::QSYMM8:
case arm_compute::DataType::QSYMM8_PER_CHANNEL:
{
CopyArmComputeITensorData(data.m_LayerOutput->GetConstTensor<int8_t>(), output);
break;
}
case arm_compute::DataType::S32:
{
CopyArmComputeITensorData(data.m_LayerOutput->GetConstTensor<int32_t>(), output);
break;
}
default:
{
ARMNN_ASSERT_MSG(false, "Unknown data type");
break;
}
}
m_RanOnce = true;
}
}
} //namespace armnn
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