| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "ClConstantWorkload.hpp" |
| |
| #include <Half.hpp> |
| #include <aclCommon/ArmComputeTensorUtils.hpp> |
| #include <cl/ClTensorHandle.hpp> |
| #include <backendsCommon/CpuTensorHandle.hpp> |
| |
| #include "ClWorkloadUtils.hpp" |
| |
| namespace armnn |
| { |
| |
| ClConstantWorkload::ClConstantWorkload(const ConstantQueueDescriptor& descriptor, const WorkloadInfo& info) |
| : BaseWorkload<ConstantQueueDescriptor>(descriptor, info) |
| , m_RanOnce(false) |
| { |
| } |
| |
| void ClConstantWorkload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_CL("ClConstantWorkload_Execute"); |
| |
| // 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::CLTensor& output = static_cast<ClTensorHandle*>(data.m_Outputs[0])->GetTensor(); |
| arm_compute::DataType computeDataType = static_cast<ClTensorHandle*>(data.m_Outputs[0])->GetDataType(); |
| |
| switch (computeDataType) |
| { |
| case arm_compute::DataType::F16: |
| { |
| CopyArmComputeClTensorData(output, data.m_LayerOutput->GetConstTensor<Half>()); |
| break; |
| } |
| case arm_compute::DataType::F32: |
| { |
| CopyArmComputeClTensorData(output, data.m_LayerOutput->GetConstTensor<float>()); |
| break; |
| } |
| case arm_compute::DataType::QASYMM8: |
| { |
| CopyArmComputeClTensorData(output, data.m_LayerOutput->GetConstTensor<uint8_t>()); |
| break; |
| } |
| default: |
| { |
| BOOST_ASSERT_MSG(false, "Unknown data type"); |
| break; |
| } |
| } |
| |
| m_RanOnce = true; |
| } |
| } |
| |
| } //namespace armnn |