| // |
| // Copyright © 2019 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "NeonDepthToSpaceWorkload.hpp" |
| |
| #include "NeonWorkloadUtils.hpp" |
| |
| #include <aclCommon/ArmComputeTensorUtils.hpp> |
| |
| #include <boost/numeric/conversion/cast.hpp> |
| #include <boost/polymorphic_pointer_cast.hpp> |
| |
| namespace armnn |
| { |
| |
| using namespace armcomputetensorutils; |
| |
| arm_compute::Status NeonDepthToSpaceWorkloadValidate(const TensorInfo& input, |
| const TensorInfo& output, |
| const DepthToSpaceDescriptor& descriptor) |
| { |
| DataLayout dataLayout = descriptor.m_DataLayout; |
| const arm_compute::TensorInfo aclInput = BuildArmComputeTensorInfo(input, dataLayout); |
| const arm_compute::TensorInfo aclOutput = BuildArmComputeTensorInfo(output, dataLayout); |
| |
| int32_t blockSize = boost::numeric_cast<int32_t>(descriptor.m_BlockSize); |
| |
| return arm_compute::NEDepthToSpaceLayer::validate(&aclInput, &aclOutput, blockSize); |
| } |
| |
| NeonDepthToSpaceWorkload::NeonDepthToSpaceWorkload(const DepthToSpaceQueueDescriptor& desc, |
| const WorkloadInfo& info) |
| : BaseWorkload<DepthToSpaceQueueDescriptor>(desc, info) |
| { |
| m_Data.ValidateInputsOutputs("NeonDepthToSpaceWorkload", 1, 1); |
| |
| arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); |
| |
| arm_compute::ITensor& input = |
| boost::polymorphic_pointer_downcast<IAclTensorHandle>(m_Data.m_Inputs[0])->GetTensor(); |
| input.info()->set_data_layout(aclDataLayout); |
| |
| int32_t blockSize = boost::numeric_cast<int32_t>(desc.m_Parameters.m_BlockSize); |
| |
| arm_compute::ITensor& output = |
| boost::polymorphic_pointer_downcast<IAclTensorHandle>(m_Data.m_Outputs[0])->GetTensor(); |
| output.info()->set_data_layout(aclDataLayout); |
| |
| m_Layer.configure(&input, &output, blockSize); |
| m_Layer.prepare(); |
| } |
| |
| void NeonDepthToSpaceWorkload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonDepthToSpaceWorkload_Execute"); |
| m_Layer.run(); |
| } |
| |
| } // namespace armnn |