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 arm_compute::CLCompileContext &clCompileContext, const bool isFastMathEnabled=false)
void	Execute () const override
arm_compute::ConvolutionMethod	GetConvolutionMethod () const
bool	SupportsTensorHandleReplacement () const override
Public Member Functions inherited from ClBaseWorkload< Convolution2dQueueDescriptor >
	ClBaseWorkload (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 void	RegisterDebugCallback (const DebugCallbackFunction &)
virtual armnn::Optional< armnn::MemoryRequirements >	GetMemoryRequirements ()

Protected Member Functions
void	Reconfigure () override

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

Detailed Description

Definition at line 31 of file ClConvolution2dWorkload.hpp.

Constructor & Destructor Documentation

ClConvolution2dWorkload()

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

Definition at line 72 of file ClConvolution2dWorkload.cpp.

    : ClBaseWorkload<Convolution2dQueueDescriptor>(descriptor, info)
    , m_ConvolutionLayer(memoryManager)
{
    ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "ClConvolution2dWorkload");
 
    const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(m_Data.m_Parameters.m_DilationX,
                                                                      m_Data.m_Parameters.m_DilationY);
 
    uint32_t numInputs = m_Data.m_Parameters.m_BiasEnabled ? 3: 2;
    m_Data.ValidateInputsOutputs("ClConvolution2dWorkload", numInputs, 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::ICLTensor& weights = static_cast<IClTensorHandle*>(m_Data.m_Inputs[1])->GetTensor();
    weights.info()->set_are_values_constant(info.m_InputTensorInfos[1].IsConstant());
 
    if (m_Data.m_Parameters.m_BiasEnabled)
    {
        arm_compute::ICLTensor& bias = static_cast<IClTensorHandle*>(m_Data.m_Inputs[2])->GetTensor();
        bias.info()->set_are_values_constant(info.m_InputTensorInfos[2].IsConstant());
        // We do not support dynamic bias
        ARMNN_ASSERT(info.m_InputTensorInfos[2].IsConstant() == true);
 
        m_BiasProxy = std::make_unique<ICLTensorProxy>(&bias);
    }
 
    // Create Proxy tensor and set the initial tensor handle to it
    m_InputProxy = std::make_unique<ICLTensorProxy>(&input);
    m_OutputProxy = std::make_unique<ICLTensorProxy>(&output);
    m_WeightsProxy = std::make_unique<ICLTensorProxy>(&weights);
 
    arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
    input.info()->set_data_layout(aclDataLayout);
    output.info()->set_data_layout(aclDataLayout);
    weights.info()->set_data_layout(aclDataLayout);
 
    arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(m_Data.m_Parameters);
 
    const arm_compute::ActivationLayerInfo activationInfo = ConvertAdditionalInfoToAclActivationLayerInfo(descriptor);
 
    {
        ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "ClConvolution2dWorkload_configure");
        m_ConvolutionLayer.configure(clCompileContext,
                                     m_InputProxy.get(),
                                     m_WeightsProxy.get(),
                                     m_BiasProxy.get(),
                                     m_OutputProxy.get(),
                                     padStrideInfo,
                                     arm_compute::WeightsInfo(),
                                     aclDilationInfo,
                                     activationInfo,
                                     isFastMathEnabled);
    }
 
    m_ConvolutionMethod =
        m_ConvolutionLayer.get_convolution_method(input.info(),
                                                  weights.info(),
                                                  output.info(),
                                                  padStrideInfo,
                                                  arm_compute::WeightsInfo(),
                                                  activationInfo,
                                                  arm_compute::CLScheduler::get().target(),
                                                  aclDilationInfo,
                                                  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("ClConvolution2dWorkload_Construct",
                                         descriptor.m_Parameters,
                                         detailsInfo,
                                         GetGuid());
}

References ARMNN_SCOPED_PROFILING_EVENT, armnn::info, and armnn::Undefined.

Member Function Documentation

Execute()

void Execute ( ) const

overridevirtual

Implements IWorkload.

Definition at line 161 of file ClConvolution2dWorkload.cpp.

{
    ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClConvolution2dWorkload_Execute", GetGuid());
    RunClFunction(m_ConvolutionLayer, CHECK_LOCATION());
}

References ARMNN_SCOPED_PROFILING_EVENT_CL_GUID, CHECK_LOCATION, BaseWorkload< Convolution2dQueueDescriptor >::GetGuid(), and armnn::RunClFunction().

GetConvolutionMethod()

arm_compute::ConvolutionMethod GetConvolutionMethod

(

)

const

Definition at line 167 of file ClConvolution2dWorkload.cpp.

{
    return m_ConvolutionMethod;
}

Reconfigure()

void Reconfigure ( )

overrideprotectedvirtual

Reimplemented from ClBaseWorkload< Convolution2dQueueDescriptor >.

Definition at line 172 of file ClConvolution2dWorkload.cpp.

{
    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();
 
    m_InputProxy->set(&input);
    m_OutputProxy->set(&output);
}

References BaseWorkload< Convolution2dQueueDescriptor >::m_Data, QueueDescriptor::m_Inputs, and QueueDescriptor::m_Outputs.

SupportsTensorHandleReplacement()

bool SupportsTensorHandleReplacement ( ) const

inlineoverridevirtual

Implements IWorkload.

Definition at line 43 of file ClConvolution2dWorkload.hpp.

    {
        // NCHW DataLayout on ACL still uses paddding for alignment on the Conv2d workload so importing is unreliable.
        if (m_Data.m_Parameters.m_DataLayout == DataLayout::NCHW)
        {
            return false;
        }
        else
        {
            return true;
        }
    }

References BaseWorkload< Convolution2dQueueDescriptor >::m_Data, Convolution2dDescriptor::m_DataLayout, QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters, and armnn::NCHW.

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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