| // |
| // Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "NeonBatchMatMulWorkload.hpp" |
| |
| #include "NeonWorkloadUtils.hpp" |
| |
| #include <armnn/utility/PolymorphicDowncast.hpp> |
| #include <aclCommon/ArmComputeUtils.hpp> |
| |
| #include <backendsCommon/WorkloadUtils.hpp> |
| |
| #include <arm_compute/core/MatMulInfo.h> |
| |
| namespace armnn |
| { |
| arm_compute::Status NeonBatchMatMulValidate(const TensorInfo& inputInfoX, |
| const TensorInfo& inputInfoY, |
| const TensorInfo& outputInfo, |
| const BatchMatMulDescriptor& descriptor, |
| const bool isFastMathEnabled, |
| const ActivationDescriptor* activationDescriptor) |
| { |
| if (descriptor.m_AdjointX || descriptor.m_AdjointY ) |
| { |
| throw Exception("Support for adjoint not implemented."); |
| } |
| if (descriptor.m_DataLayoutX != armnn::DataLayout::NCHW || descriptor.m_DataLayoutY != armnn::DataLayout::NCHW ) |
| { |
| throw Exception("Only supported the MatMul in the last 2 dimensions"); |
| } |
| |
| arm_compute::TensorInfo aclInputInfoX = armcomputetensorutils::BuildArmComputeTensorInfo(inputInfoX); |
| arm_compute::TensorInfo aclInputInfoY = armcomputetensorutils::BuildArmComputeTensorInfo(inputInfoY); |
| arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(outputInfo); |
| |
| // GeMM dispatches kernel handles dynamic inputs differently to static so this flag needs to be set |
| aclInputInfoX.set_are_values_constant(false); |
| aclInputInfoY.set_are_values_constant(false); |
| |
| const arm_compute::ActivationLayerInfo activationInfo = ConvertActivationDescriptorToAclActivationLayerInfo( |
| activationDescriptor); |
| |
| arm_compute::MatMulInfo matMulInfo; |
| matMulInfo.adj_lhs(descriptor.m_TransposeX); |
| matMulInfo.adj_rhs(descriptor.m_TransposeY); |
| matMulInfo.fused_activation(activationInfo); |
| |
| arm_compute::CpuMatMulSettings settings; |
| settings.fast_math(isFastMathEnabled); |
| |
| return arm_compute::NEMatMul::validate(&aclInputInfoX, &aclInputInfoY, &aclOutputInfo, matMulInfo, settings); |
| } |
| |
| NeonBatchMatMulWorkload::NeonBatchMatMulWorkload(const BatchMatMulQueueDescriptor& descriptor, |
| const WorkloadInfo& info, |
| const bool isFastMathEnabled) |
| : NeonBaseWorkload<BatchMatMulQueueDescriptor>(descriptor, info) |
| { |
| if (descriptor.m_Parameters.m_AdjointX || descriptor.m_Parameters.m_AdjointY ) |
| { |
| throw Exception("Support for adjoint not implemented."); |
| } |
| if (descriptor.m_Parameters.m_DataLayoutX != armnn::DataLayout::NCHW |
| || descriptor.m_Parameters.m_DataLayoutY != armnn::DataLayout::NCHW ) |
| { |
| throw Exception("Only supported the MatMul in the last 2 dimensions"); |
| } |
| |
| m_Data.ValidateInputsOutputs("NeonBatchMatMulWorkload", 2, 1); |
| |
| arm_compute::ITensor& inputX = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); |
| arm_compute::ITensor& inputY = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); |
| arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); |
| |
| // GeMM dispatches kernel handles dynamic inputs differently to static so this flag needs to be set |
| inputX.info()->set_are_values_constant(false); |
| inputY.info()->set_are_values_constant(false); |
| |
| const arm_compute::ActivationLayerInfo activationInfo = ConvertAdditionalInfoToAclActivationLayerInfo(descriptor); |
| |
| arm_compute::MatMulInfo matMulInfo; |
| matMulInfo.adj_lhs(descriptor.m_Parameters.m_TransposeX); |
| matMulInfo.adj_rhs(descriptor.m_Parameters.m_TransposeY); |
| matMulInfo.fused_activation(activationInfo); |
| |
| arm_compute::CpuMatMulSettings settings; |
| settings.fast_math(isFastMathEnabled); |
| |
| m_MatMulLayer.configure(&inputX, &inputY, &output, matMulInfo, settings); |
| |
| // Report Profiling Details |
| WorkloadInfo detailsInfo; |
| detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos; |
| detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos; |
| ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonBatchMatMulWorkload_Construct", |
| descriptor.m_Parameters, |
| detailsInfo, |
| GetGuid()); |
| } |
| |
| void NeonBatchMatMulWorkload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonBatchMatMulWorkload_Execute", this->GetGuid()); |
| m_MatMulLayer.run(); |
| } |
| } //namespace armnn |