NeonConvolution2dWorkload Class Reference

#include <NeonConvolution2dWorkload.hpp>

Inheritance diagram for NeonConvolution2dWorkload:

Public Member Functions
	NeonConvolution2dWorkload (const Convolution2dQueueDescriptor &descriptor, const WorkloadInfo &info, std::shared_ptr< arm_compute::MemoryManagerOnDemand > &memoryManager, const bool isFastMathENabled=false)
void	Execute () const override
arm_compute::ConvolutionMethod	GetConvolutionMethod () const
Public Member Functions inherited from NeonBaseWorkload< Convolution2dQueueDescriptor >
	NeonBaseWorkload (const Convolution2dQueueDescriptor &descriptor, const WorkloadInfo &info)
void	ReplaceInputTensorHandle (ITensorHandle *tensorHandle, unsigned int slot) override
void	ReplaceOutputTensorHandle (ITensorHandle *tensorHandle, unsigned int slot) override
Public Member Functions inherited from BaseWorkload< Convolution2dQueueDescriptor >
	BaseWorkload (const Convolution2dQueueDescriptor &descriptor, const WorkloadInfo &info)
void	ExecuteAsync (ExecutionData &executionData) override
void	PostAllocationConfigure () override
const Convolution2dQueueDescriptor &	GetData () const
arm::pipe::ProfilingGuid	GetGuid () const final
virtual bool	SupportsTensorHandleReplacement () const override
Public Member Functions inherited from IWorkload
virtual	~IWorkload ()
virtual arm::pipe::ProfilingGuid	GetGuid () const =0
virtual bool	SupportsTensorHandleReplacement () const =0
virtual void	RegisterDebugCallback (const DebugCallbackFunction &)
virtual armnn::Optional< armnn::MemoryRequirements >	GetMemoryRequirements ()

Additional Inherited Members
Protected Member Functions inherited from NeonBaseWorkload< Convolution2dQueueDescriptor >
virtual void	Reconfigure ()
Protected Attributes inherited from BaseWorkload< Convolution2dQueueDescriptor >
Convolution2dQueueDescriptor	m_Data
const arm::pipe::ProfilingGuid	m_Guid

Detailed Description

Definition at line 27 of file NeonConvolution2dWorkload.hpp.

Constructor & Destructor Documentation

NeonConvolution2dWorkload()

NeonConvolution2dWorkload	(	const Convolution2dQueueDescriptor &	descriptor,
		const WorkloadInfo &	info,
		std::shared_ptr< arm_compute::MemoryManagerOnDemand > &	memoryManager,
		const bool	isFastMathENabled = false
	)

Definition at line 73 of file NeonConvolution2dWorkload.cpp.

    : NeonBaseWorkload<Convolution2dQueueDescriptor>(descriptor, info)
{
    using arm_compute::NEConvolutionLayer;
 
    uint32_t numInputs = m_Data.m_Parameters.m_BiasEnabled ? 3: 2;
    m_Data.ValidateInputsOutputs("NeonConvolution2dWorkload", numInputs, 1);
 
    arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
    arm_compute::ITensor& output = PolymorphicDowncast<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, info.m_InputTensorInfos[1], m_Data.m_Parameters.m_DataLayout);
    if (m_Data.m_Parameters.m_BiasEnabled)
    {
        m_BiasTensor = std::make_unique<arm_compute::Tensor>();
        BuildArmComputeTensor(*m_BiasTensor, info.m_InputTensorInfos[2], m_Data.m_Parameters.m_DataLayout);
    }
 
    arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(m_Data.m_Parameters);
 
    const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(m_Data.m_Parameters.m_DilationX,
                                                                      m_Data.m_Parameters.m_DilationY);
 
    const arm_compute::ActivationLayerInfo activationInfo = ConvertAdditionalInfoToAclActivationLayerInfo(descriptor);
 
    auto convolutionLayer = std::make_unique<arm_compute::NEConvolutionLayer>(memoryManager);
    convolutionLayer->configure(&input,
                                m_KernelTensor.get(),
                                m_BiasTensor.get(),
                                &output,
                                padStrideInfo,
                                arm_compute::WeightsInfo(),
                                aclDilationInfo,
                                activationInfo,
                                isFastMathEnabled);
 
    m_ConvolutionMethod =
        convolutionLayer->get_convolution_method(input.info(),
                                                 m_KernelTensor->info(),
                                                 output.info(),
                                                 padStrideInfo,
                                                 arm_compute::WeightsInfo(),
                                                 aclDilationInfo,
                                                 activationInfo,
                                                 isFastMathEnabled);
 
    // Add details for profiling output
    WorkloadInfo detailsInfo;
 
    detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos;
    detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos;
    detailsInfo.m_WeightsTensorInfo = armnn::Optional<armnn::TensorInfo>(info.m_InputTensorInfos[1]);
    detailsInfo.m_ConvolutionMethod = armnn::Optional<std::string>(GetConvolutionMethodString(m_ConvolutionMethod));
 
    if (descriptor.m_Parameters.m_BiasEnabled)
    {
        detailsInfo.m_BiasTensorInfo = armnn::Optional<armnn::TensorInfo>(info.m_InputTensorInfos[2]);
    }
 
    // Report Profiling Details
    ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonConvolution2dWorkload_Construct",
                                         descriptor.m_Parameters,
                                         detailsInfo,
                                         GetGuid());
 
    m_ConvolutionLayer.reset(convolutionLayer.release());
 
    ARMNN_ASSERT(m_ConvolutionLayer);
    m_KernelTensorInfo = info.m_InputTensorInfos[1];
 
    if (m_Data.m_Parameters.m_BiasEnabled)
    {
        m_BiasTensorInfo = info.m_InputTensorInfos[2];
    }
}

References armnn::info, Convolution2dDescriptor::m_BiasEnabled, BaseWorkload< Convolution2dQueueDescriptor >::m_Data, QueueDescriptor::m_Inputs, QueueDescriptor::m_Outputs, QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters, and QueueDescriptor::ValidateInputsOutputs().

Member Function Documentation

Execute()

void Execute ( ) const

overridevirtual

Implements IWorkload.

Definition at line 158 of file NeonConvolution2dWorkload.cpp.

{
    ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonConvolution2dWorkload_Execute", this->GetGuid());
    // The constant tensors may not be fully in place until the workload is Executed
    if (!prepared)
    {
        InitializeArmComputeTensorData(*m_KernelTensor, m_KernelTensorInfo, m_Data.m_Inputs[1]);
 
        if (m_Data.m_Parameters.m_BiasEnabled)
        {
            InitializeArmComputeTensorData(*m_BiasTensor, m_BiasTensorInfo, m_Data.m_Inputs[2]);
        }
        m_ConvolutionLayer->prepare();
        FreeTensorIfUnused(m_KernelTensor);
        FreeTensorIfUnused(m_BiasTensor);
        prepared = true;
    }
    m_ConvolutionLayer->run();
}

References ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID, BaseWorkload< Convolution2dQueueDescriptor >::GetGuid(), armnn::InitializeArmComputeTensorData(), Convolution2dDescriptor::m_BiasEnabled, BaseWorkload< Convolution2dQueueDescriptor >::m_Data, QueueDescriptor::m_Inputs, and QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters.

GetConvolutionMethod()

arm_compute::ConvolutionMethod GetConvolutionMethod

(

)

const

Definition at line 178 of file NeonConvolution2dWorkload.cpp.

{
    return m_ConvolutionMethod;
}

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The documentation for this class was generated from the following files:

• src/backends/neon/workloads/NeonConvolution2dWorkload.hpp
• src/backends/neon/workloads/NeonConvolution2dWorkload.cpp