ClConvolution2dWorkload Class Reference

#include <ClConvolution2dWorkload.hpp>

Inheritance diagram for ClConvolution2dWorkload:

Public Member Functions
	ClConvolution2dWorkload (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 BaseWorkload< Convolution2dQueueDescriptor >
	BaseWorkload (const Convolution2dQueueDescriptor &descriptor, const WorkloadInfo &info)
void	PostAllocationConfigure () override
const Convolution2dQueueDescriptor &	GetData () const
profiling::ProfilingGuid	GetGuid () const final
Public Member Functions inherited from IWorkload
virtual	~IWorkload ()
virtual void	RegisterDebugCallback (const DebugCallbackFunction &)

Additional Inherited Members
Protected Attributes inherited from BaseWorkload< Convolution2dQueueDescriptor >
const Convolution2dQueueDescriptor	m_Data
const profiling::ProfilingGuid	m_Guid

Detailed Description

Definition at line 29 of file ClConvolution2dWorkload.hpp.

Constructor & Destructor Documentation

ClConvolution2dWorkload()

ClConvolution2dWorkload	(	const Convolution2dQueueDescriptor &	descriptor,
		const WorkloadInfo &	info,
		std::shared_ptr< arm_compute::MemoryManagerOnDemand > &	memoryManager,
		const bool	isFastMathEnabled = false
	)

Definition at line 65 of file ClConvolution2dWorkload.cpp.

References ConstCpuTensorHandle::GetTensorInfo(), BaseWorkload< Convolution2dQueueDescriptor >::m_Data, and Convolution2dQueueDescriptor::m_Weight.

    : BaseWorkload<Convolution2dQueueDescriptor>(descriptor, info)
    , m_ConvolutionLayer(memoryManager)
{
    // todo: check tensor shapes match.
    const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo();

    m_KernelTensor = std::make_unique<arm_compute::CLTensor>();
    BuildArmComputeTensor(*m_KernelTensor, weightInfo, m_Data.m_Parameters.m_DataLayout);

    const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(m_Data.m_Parameters.m_DilationX,
                                                                      m_Data.m_Parameters.m_DilationY);

    if (m_Data.m_Parameters.m_BiasEnabled)
    {
        m_BiasTensor = std::make_unique<arm_compute::CLTensor>();
        BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout);
    }

    m_Data.ValidateInputsOutputs("ClConvolution2dWorkload", 1, 1);

    arm_compute::ICLTensor& input  = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
    arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(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);

    const arm_compute::ActivationLayerInfo activationInfo = ConvertAdditionalInfoToAclActivationLayerInfo(descriptor);

    m_ConvolutionLayer.configure(&input,
                                 m_KernelTensor.get(),
                                 m_BiasTensor.get(),
                                 &output,
                                 padStrideInfo,
                                 arm_compute::WeightsInfo(),
                                 aclDilationInfo,
                                 activationInfo,
                                 isFastMathEnabled);

    m_ConvolutionMethod =
        m_ConvolutionLayer.get_convolution_method(input.info(),
                                                  m_KernelTensor->info(),
                                                  output.info(),
                                                  padStrideInfo,
                                                  arm_compute::WeightsInfo(),
                                                  activationInfo,
                                                  arm_compute::CLScheduler::get().target(),
                                                  aclDilationInfo,
                                                  isFastMathEnabled);

    InitializeArmComputeClTensorData(*m_KernelTensor, m_Data.m_Weight);

    if (m_BiasTensor)
    {
        InitializeArmComputeClTensorData(*m_BiasTensor, m_Data.m_Bias);
    }

    // Force Compute Library to perform the necessary copying and reshaping, after which
    // delete all the input tensors that will no longer be needed
    m_ConvolutionLayer.prepare();
    FreeUnusedTensors();
}

Member Function Documentation

Execute()

void Execute ( ) const

overridevirtual

Implements IWorkload.

Definition at line 134 of file ClConvolution2dWorkload.cpp.

References ARMNN_SCOPED_PROFILING_EVENT_CL, CHECK_LOCATION, and armnn::RunClFunction().

{
    ARMNN_SCOPED_PROFILING_EVENT_CL("ClConvolution2dWorkload_Execute");
    RunClFunction(m_ConvolutionLayer, CHECK_LOCATION());
}

GetConvolutionMethod()

arm_compute::ConvolutionMethod GetConvolutionMethod

(

)

const

Definition at line 140 of file ClConvolution2dWorkload.cpp.

{
    return m_ConvolutionMethod;
}

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

• src/backends/cl/workloads/ClConvolution2dWorkload.hpp
• src/backends/cl/workloads/ClConvolution2dWorkload.cpp