Convolution2dQueueDescriptor Struct Reference

#include <WorkloadData.hpp>

Inheritance diagram for Convolution2dQueueDescriptor:

Public Member Functions
void	Validate (const WorkloadInfo &workloadInfo) const
Public Member Functions inherited from QueueDescriptorWithParameters< Convolution2dDescriptor >
virtual	~QueueDescriptorWithParameters ()=default
Public Member Functions inherited from QueueDescriptor
virtual	~QueueDescriptor ()=default
void	ValidateTensorNumDimensions (const TensorInfo &tensor, std::string const &descName, unsigned int numDimensions, std::string const &tensorName) const
void	ValidateTensorNumDimNumElem (const TensorInfo &tensorInfo, unsigned int numDimension, unsigned int numElements, std::string const &tensorName) const
void	ValidateInputsOutputs (const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
template<typename T >
const T *	GetAdditionalInformation () const

Additional Inherited Members
Public Attributes inherited from QueueDescriptorWithParameters< Convolution2dDescriptor >
Convolution2dDescriptor	m_Parameters
Public Attributes inherited from QueueDescriptor
std::vector< ITensorHandle * >	m_Inputs
std::vector< ITensorHandle * >	m_Outputs
void *	m_AdditionalInfoObject
bool	m_AllowExpandedDims = false
Protected Member Functions inherited from QueueDescriptorWithParameters< Convolution2dDescriptor >
	QueueDescriptorWithParameters ()=default
	QueueDescriptorWithParameters (QueueDescriptorWithParameters const &)=default
QueueDescriptorWithParameters &	operator= (QueueDescriptorWithParameters const &)=default
Protected Member Functions inherited from QueueDescriptor
	QueueDescriptor ()
	QueueDescriptor (QueueDescriptor const &)=default
QueueDescriptor &	operator= (QueueDescriptor const &)=default

Detailed Description

Definition at line 205 of file WorkloadData.hpp.

Member Function Documentation

Validate()

void Validate

(

const WorkloadInfo &

workloadInfo

)

const

Definition at line 1270 of file WorkloadData.cpp.

{
    const std::string descriptorName{"Convolution2dQueueDescriptor"};
 
    uint32_t numInputs = 2;
    if (m_Parameters.m_BiasEnabled)
    {
        numInputs = 3;
    }
 
    ValidateNumInputs(workloadInfo,  descriptorName, numInputs);
    ValidateNumOutputs(workloadInfo, descriptorName, 1);
 
    const TensorInfo& inputTensorInfo  = workloadInfo.m_InputTensorInfos[0];
    const TensorInfo& outputTensorInfo = workloadInfo.m_OutputTensorInfos[0];
 
    ValidateTensorNumDimensions(inputTensorInfo,  descriptorName, 4, "input");
    ValidateTensorNumDimensions(outputTensorInfo, descriptorName, 4, "output");
 
    const TensorInfo& weightTensorInfo = workloadInfo.m_InputTensorInfos[1];
 
    ValidateTensorNumDimensions(weightTensorInfo, descriptorName, 4, "weight");
 
    ValidateWeightDataType(inputTensorInfo, weightTensorInfo, descriptorName);
 
    Optional<TensorInfo> optionalBiasTensorInfo;
    if (m_Parameters.m_BiasEnabled)
    {
        optionalBiasTensorInfo = MakeOptional<TensorInfo>(workloadInfo.m_InputTensorInfos[2]);
        const TensorInfo& biasTensorInfo = optionalBiasTensorInfo.value();
 
        ValidateTensorDataType(biasTensorInfo, GetBiasDataType(inputTensorInfo.GetDataType()), descriptorName, "bias");
        ValidateBiasTensorQuantization(biasTensorInfo, inputTensorInfo, weightTensorInfo, descriptorName);
    }
 
    if (m_Parameters.m_StrideX <= 0 || m_Parameters.m_StrideY <= 0  )
    {
        throw InvalidArgumentException(
            fmt::format("{}: strideX (provided {}) and strideY (provided {}) "
                        "cannot be either negative or 0.",
                        descriptorName, m_Parameters.m_StrideX, m_Parameters.m_StrideY));
    }
 
    ValidatePerAxisQuantization(inputTensorInfo,
                                outputTensorInfo,
                                weightTensorInfo,
                                optionalBiasTensorInfo,
                                descriptorName);
 
    std::vector<DataType> supportedTypes =
    {
        DataType::BFloat16,
        DataType::Float16,
        DataType::Float32,
        DataType::QAsymmS8,
        DataType::QAsymmU8,
        DataType::QSymmS16,
        DataType::QSymmS8
    };
 
    ValidateDataTypes(inputTensorInfo, supportedTypes, descriptorName);
 
    // For Convolution2d, we allow to have BFloat16 input with Float32 output for optimization.
    if (inputTensorInfo.GetDataType() == DataType::BFloat16)
    {
        if (outputTensorInfo.GetDataType() != DataType::BFloat16 && outputTensorInfo.GetDataType() != DataType::Float32)
        {
            throw InvalidArgumentException(descriptorName  + ": " + " Output tensor type must be BFloat16 or Float32 "
                                           "for BFloat16 input.");
        }
    }
    else
    {
        ValidateTensorDataTypesMatch(inputTensorInfo, outputTensorInfo, descriptorName, "input", "output");
    }
}

References armnn::BFloat16, armnn::Float16, armnn::Float32, armnn::GetBiasDataType(), TensorInfo::GetDataType(), Convolution2dDescriptor::m_BiasEnabled, WorkloadInfo::m_InputTensorInfos, WorkloadInfo::m_OutputTensorInfos, QueueDescriptorWithParameters< Convolution2dDescriptor >::m_Parameters, Convolution2dDescriptor::m_StrideX, Convolution2dDescriptor::m_StrideY, armnn::QAsymmS8, armnn::QAsymmU8, armnn::QSymmS16, armnn::QSymmS8, QueueDescriptor::ValidateTensorNumDimensions(), and OptionalReferenceSwitch< std::is_reference< T >::value, T >::value().

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

• include/armnn/backends/WorkloadData.hpp
• src/backends/backendsCommon/WorkloadData.cpp