| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| #include "NeonTransposeConvolution2dWorkload.hpp" |
| |
| #include "NeonWorkloadUtils.hpp" |
| |
| #include <Profiling.hpp> |
| |
| #include <armnn/Types.hpp> |
| |
| #include <aclCommon/ArmComputeTensorUtils.hpp> |
| |
| #include <backendsCommon/CpuTensorHandle.hpp> |
| |
| #include <neon/workloads/NeonWorkloadUtils.hpp> |
| |
| #include <boost/cast.hpp> |
| |
| namespace armnn |
| { |
| |
| using namespace armcomputetensorutils; |
| |
| arm_compute::Status NeonTransposeConvolution2dWorkloadValidate(const TensorInfo& input, |
| const TensorInfo& output, |
| const TransposeConvolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases) |
| { |
| const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); |
| const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); |
| const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout); |
| |
| arm_compute::TensorInfo aclBiasesInfo; |
| arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr; |
| |
| if (descriptor.m_BiasEnabled) |
| { |
| BOOST_ASSERT(biases.has_value()); |
| |
| aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout); |
| optionalAclBiasesInfo = &aclBiasesInfo; |
| } |
| |
| arm_compute::PadStrideInfo layerInfo = BuildArmComputePadStrideInfo(descriptor); |
| |
| return arm_compute::NEDeconvolutionLayer::validate(&aclInputInfo, |
| &aclWeightsInfo, |
| optionalAclBiasesInfo, |
| &aclOutputInfo, |
| layerInfo); |
| } |
| |
| NeonTransposeConvolution2dWorkload::NeonTransposeConvolution2dWorkload( |
| const TransposeConvolution2dQueueDescriptor& descriptor, const WorkloadInfo& info, |
| std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager) |
| : BaseWorkload<TransposeConvolution2dQueueDescriptor>(descriptor, info) |
| { |
| m_Data.ValidateInputsOutputs("NeonTransposeConvolution2dWorkload", 1, 1); |
| |
| arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); |
| arm_compute::ITensor& output = boost::polymorphic_downcast<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); |
| |
| m_KernelTensor = std::make_unique<arm_compute::Tensor>(); |
| BuildArmComputeTensor(*m_KernelTensor, m_Data.m_Weight->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout); |
| |
| if (m_Data.m_Parameters.m_BiasEnabled) |
| { |
| m_BiasTensor = std::make_unique<arm_compute::Tensor>(); |
| BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout); |
| } |
| |
| arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(m_Data.m_Parameters); |
| |
| m_Layer = std::make_unique<arm_compute::NEDeconvolutionLayer>(memoryManager); |
| m_Layer->configure(&input, m_KernelTensor.get(), m_BiasTensor.get(), &output, padStrideInfo); |
| |
| BOOST_ASSERT(m_Layer); |
| |
| InitializeArmComputeTensorData(*m_KernelTensor, m_Data.m_Weight); |
| |
| if (m_Data.m_Parameters.m_BiasEnabled) |
| { |
| InitializeArmComputeTensorData(*m_BiasTensor, m_Data.m_Bias); |
| } |
| |
| m_Layer->prepare(); |
| FreeUnusedTensors(); |
| } |
| |
| void NeonTransposeConvolution2dWorkload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonTransposeConvolution2dWorkload_Execute"); |
| m_Layer->run(); |
| } |
| |
| void NeonTransposeConvolution2dWorkload::FreeUnusedTensors() |
| { |
| FreeTensorIfUnused(m_KernelTensor); |
| FreeTensorIfUnused(m_BiasTensor); |
| } |
| |
| } // namespace armnn |