NeonBatchMatMulWorkload.cpp

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//
// 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/function_info/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);
 
    arm_compute::CpuMatMulSettings settings;
    settings.fast_math(isFastMathEnabled);
 
    return arm_compute::NEMatMul::validate(&aclInputInfoX, &aclInputInfoY, &aclOutputInfo, matMulInfo, settings,
                                           activationInfo);
}
 
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);
 
    arm_compute::CpuMatMulSettings settings;
    settings.fast_math(isFastMathEnabled);
 
    m_MatMulLayer.configure(&inputX, &inputY, &output, matMulInfo, settings, activationInfo);
 
    // 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_NAME_GUID("NeonBatchMatMulWorkload_Execute");
    m_MatMulLayer.run();
}
} //namespace armnn