// // Copyright © 2017 Arm Ltd. All rights reserved. // SPDX-License-Identifier: MIT // #include "RefConvolution2dWorkload.hpp" #include "ConvImpl.hpp" #include "RefWorkloadUtils.hpp" #include "Profiling.hpp" namespace armnn { RefConvolution2dWorkload::RefConvolution2dWorkload(const Convolution2dQueueDescriptor& descriptor, const WorkloadInfo& info) : RefBaseWorkload(descriptor, info) { WorkloadInfo detailsInfo; detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos; detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos; // Report Profiling Details ARMNN_REPORT_PROFILING_WORKLOAD_DESC("RefConvolution2dWorkload_Construct", descriptor.m_Parameters, detailsInfo, this->GetGuid()); } void RefConvolution2dWorkload::PostAllocationConfigure() { PostAllocationConfigure(m_Data.m_Inputs, m_Data.m_Outputs); } void RefConvolution2dWorkload::PostAllocationConfigure(std::vector inputs, std::vector outputs) { const TensorInfo& inputInfo = GetTensorInfo(inputs[0]); ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1); m_InputShape = inputInfo.GetShape(); const TensorInfo& rFilterInfo = GetTensorInfo(inputs[1]); ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1); m_FilterShape = rFilterInfo.GetShape(); m_FilterDecoder = MakeDecoder(rFilterInfo); if (m_Data.m_Parameters.m_BiasEnabled) { const TensorInfo& biasInfo = GetTensorInfo(inputs[2]); m_BiasDecoder = MakeDecoder(biasInfo); } const TensorInfo& outputInfo = GetTensorInfo(outputs[0]); m_OutputShape = outputInfo.GetShape(); } void RefConvolution2dWorkload::Execute() const { Execute(m_Data.m_Inputs, m_Data.m_Outputs); } void RefConvolution2dWorkload::ExecuteAsync(WorkingMemDescriptor& workingMemDescriptor) { PostAllocationConfigure(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs); Execute(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs); } void RefConvolution2dWorkload::Execute(std::vector inputs, std::vector outputs) const { ARMNN_SCOPED_PROFILING_EVENT_GUID(Compute::CpuRef, "RefConvolution2dWorkload_Execute", this->GetGuid()); std::unique_ptr> inputDecoder = MakeDecoder(GetTensorInfo(inputs[0]), inputs[0]->Map()); std::unique_ptr> outputEncoder = MakeEncoder(GetTensorInfo(outputs[0]), outputs[0]->Map()); m_FilterDecoder->Reset(inputs[1]->Map()); if (m_Data.m_Parameters.m_BiasEnabled) { m_BiasDecoder->Reset(inputs[2]->Map()); } Convolve(m_InputShape, *inputDecoder, m_OutputShape, *outputEncoder, m_FilterShape, *m_FilterDecoder, m_Data.m_Parameters.m_BiasEnabled, m_BiasDecoder.get(), m_Data.m_Parameters.m_DataLayout, m_Data.m_Parameters.m_PadTop, m_Data.m_Parameters.m_PadLeft, m_Data.m_Parameters.m_StrideX, m_Data.m_Parameters.m_StrideY, m_Data.m_Parameters.m_DilationX, m_Data.m_Parameters.m_DilationY); } } //namespace armnn