| // |
| // Copyright © 2020, 2023 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "NeonBatchToSpaceNdWorkload.hpp" |
| |
| #include "NeonWorkloadUtils.hpp" |
| |
| #include <armnn/utility/NumericCast.hpp> |
| #include <armnn/utility/PolymorphicDowncast.hpp> |
| |
| #include <ResolveType.hpp> |
| |
| namespace armnn |
| { |
| |
| using namespace armcomputetensorutils; |
| |
| arm_compute::Status NeonBatchToSpaceNdWorkloadValidate(const TensorInfo& input, |
| const TensorInfo& output, |
| const BatchToSpaceNdDescriptor& descriptor) |
| { |
| const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); |
| const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); |
| |
| // ArmNN blockShape is [H, W] Cl asks for W, H |
| int32_t blockHeight = armnn::numeric_cast<int32_t>(descriptor.m_BlockShape[0]); |
| int32_t blockWidth = armnn::numeric_cast<int32_t>(descriptor.m_BlockShape[1]); |
| |
| const arm_compute::CropInfo cropInfo = BuildArmComputeCropInfo(descriptor); |
| |
| const arm_compute::Status aclStatus = arm_compute::NEBatchToSpaceLayer::validate(&aclInputInfo, |
| blockWidth, |
| blockHeight, |
| &aclOutputInfo, |
| cropInfo); |
| return aclStatus; |
| } |
| |
| NeonBatchToSpaceNdWorkload::NeonBatchToSpaceNdWorkload(const BatchToSpaceNdQueueDescriptor& descriptor, |
| const WorkloadInfo& info) |
| : NeonBaseWorkload<BatchToSpaceNdQueueDescriptor>(descriptor, info) |
| { |
| // Report Profiling Details |
| ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonBatchToSpaceWorkload_Construct", |
| descriptor.m_Parameters, |
| info, |
| this->GetGuid()); |
| |
| m_Data.ValidateInputsOutputs("NeonBatchToSpaceNdWorkload", 1, 1); |
| |
| arm_compute::ITensor& input = |
| armnn::PolymorphicPointerDowncast<IAclTensorHandle>(m_Data.m_Inputs[0])->GetTensor(); |
| arm_compute::ITensor& output = |
| armnn::PolymorphicPointerDowncast<IAclTensorHandle>(m_Data.m_Outputs[0])->GetTensor(); |
| |
| arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); |
| input.info()->set_data_layout(aclDataLayout); |
| output.info()->set_data_layout(aclDataLayout); |
| |
| // ArmNN blockShape is [H, W] Cl asks for W, H |
| int32_t blockHeight = armnn::numeric_cast<int32_t>(descriptor.m_Parameters.m_BlockShape[0]); |
| int32_t blockWidth = armnn::numeric_cast<int32_t>(descriptor.m_Parameters.m_BlockShape[1]); |
| |
| const arm_compute::CropInfo cropInfo = BuildArmComputeCropInfo(descriptor.m_Parameters); |
| |
| m_Layer.reset(new arm_compute::NEBatchToSpaceLayer()); |
| m_Layer->configure(&input, blockWidth, blockHeight, &output, cropInfo); |
| m_Layer->prepare(); |
| } |
| |
| void NeonBatchToSpaceNdWorkload::Execute() const |
| { |
| if (m_Layer) |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonSpaceToBatchNdWorkload_Execute", this->GetGuid()); |
| m_Layer->run(); |
| } |
| } |
| |
| } //namespace armnn |