// // Copyright © 2017 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // #include "ClTransposeConvolution2dWorkload.hpp" #include "ClWorkloadUtils.hpp" #include #include #include #include #include #include #include namespace armnn { using namespace armcomputetensorutils; arm_compute::Status ClTransposeConvolution2dWorkloadValidate(const TensorInfo& input, const TensorInfo& output, const TransposeConvolution2dDescriptor& descriptor, const TensorInfo& weights, const Optional& biases) { arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout); arm_compute::TensorInfo aclBiasesInfo; arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr; if (descriptor.m_BiasEnabled) { ARMNN_ASSERT(biases.has_value()); aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout); optionalAclBiasesInfo = &aclBiasesInfo; } arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(descriptor); return arm_compute::CLDeconvolutionLayer::validate(&aclInputInfo, &aclWeightsInfo, optionalAclBiasesInfo, &aclOutputInfo, padStrideInfo); } ClTransposeConvolution2dWorkload::ClTransposeConvolution2dWorkload( const TransposeConvolution2dQueueDescriptor& descriptor, const WorkloadInfo& info, std::shared_ptr& memoryManager, const arm_compute::CLCompileContext& clCompileContext) : ClBaseWorkload(descriptor, info) , m_Layer(memoryManager) { // Add details for profiling output WorkloadInfo detailsInfo; detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos; detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos; detailsInfo.m_WeightsTensorInfo = armnn::Optional(descriptor.m_Weight->GetTensorInfo()); if (descriptor.m_Parameters.m_BiasEnabled) { detailsInfo.m_BiasTensorInfo = armnn::Optional(descriptor.m_Bias->GetTensorInfo()); } // Report Profiling Details ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClTransposeConvolution2dWorkload_Construct", descriptor.m_Parameters, detailsInfo, this->GetGuid()); const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo(); m_WeightsTensor = std::make_unique(); BuildArmComputeTensor(*m_WeightsTensor, weightInfo, m_Data.m_Parameters.m_DataLayout); if (m_Data.m_Parameters.m_BiasEnabled) { m_BiasesTensor = std::make_unique(); BuildArmComputeTensor(*m_BiasesTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout); } m_Data.ValidateInputsOutputs("ClTransposeConvolution2dWorkload", 1, 1); arm_compute::ICLTensor& input = static_cast(m_Data.m_Inputs[0])->GetTensor(); arm_compute::ICLTensor& output = static_cast(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); arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(m_Data.m_Parameters); { ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "ClTransposeConvolution2dWorkload_configure"); m_Layer.configure(clCompileContext, &input, m_WeightsTensor.get(), m_BiasesTensor.get(), &output, padStrideInfo); } InitializeArmComputeClTensorData(*m_WeightsTensor, m_Data.m_Weight); if (m_BiasesTensor) { InitializeArmComputeClTensorData(*m_BiasesTensor, m_Data.m_Bias); } m_Layer.prepare(); FreeUnusedTensors(); } void ClTransposeConvolution2dWorkload::Execute() const { ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClTransposeConvolution2dWorkload_Execute", this->GetGuid()); RunClFunction(m_Layer, CHECK_LOCATION()); } void ClTransposeConvolution2dWorkload::FreeUnusedTensors() { FreeTensorIfUnused(m_WeightsTensor); FreeTensorIfUnused(m_BiasesTensor); } } // namespace armnn