SpaceToBatchNdQueueDescriptor Struct Reference

#include <WorkloadData.hpp>

Inheritance diagram for SpaceToBatchNdQueueDescriptor:

Public Member Functions
void	Validate (const WorkloadInfo &workloadInfo) const
Public Member Functions inherited from QueueDescriptorWithParameters< SpaceToBatchNdDescriptor >
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< SpaceToBatchNdDescriptor >
SpaceToBatchNdDescriptor	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< SpaceToBatchNdDescriptor >
	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 380 of file WorkloadData.hpp.

Member Function Documentation

Validate()

void Validate

(

const WorkloadInfo &

workloadInfo

)

const

Definition at line 1808 of file WorkloadData.cpp.

{
    const std::string descriptorName{"SpaceToBatchNdQueueDescriptor"};
 
    ValidateNumInputs(workloadInfo,  descriptorName, 1);
    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");
 
    if (m_Parameters.m_BlockShape.size() != 2)
    {
        throw InvalidArgumentException(descriptorName + ": Block Shape must contain 2 spatial dimensions.");
    }
 
    if (m_Parameters.m_BlockShape.size() != m_Parameters.m_PadList.size())
    {
        throw InvalidArgumentException(descriptorName + ": Pad List must contain the same number of "
                                       "dimensions as Block Shape.");
    }
 
    const TensorShape& inputShape = inputTensorInfo.GetShape();
 
    std::pair<unsigned int, unsigned int> heightPad = m_Parameters.m_PadList[0];
    std::pair<unsigned int, unsigned int> widthPad  = m_Parameters.m_PadList[1];
 
    DataLayoutIndexed dimensionIndices(m_Parameters.m_DataLayout);
 
    const unsigned int inputWidth  = inputShape[dimensionIndices.GetWidthIndex()] +
                                     widthPad.first + widthPad.second;
    const unsigned int inputHeight = inputShape[dimensionIndices.GetHeightIndex()] +
                                     heightPad.first + heightPad.second;
 
    const unsigned int numInputElements  = inputShape[0] * inputHeight * inputWidth *
                                           inputShape[dimensionIndices.GetChannelsIndex()];
    const unsigned int numOutputElements = outputTensorInfo.GetNumElements();
 
    if (numOutputElements != numInputElements)
    {
        throw InvalidArgumentException(descriptorName + ": Input tensor has " +
            to_string(numInputElements) + " after padding but output tensor has " +
            to_string(numOutputElements) + " elements.");
    }
 
    if (inputHeight % m_Parameters.m_BlockShape[0] != 0 || inputWidth % m_Parameters.m_BlockShape[1] != 0)
    {
        throw InvalidArgumentException(descriptorName + ": Input shape after padding must be "
                                       "divisible by Block Shape in all spatial dimensions");
    }
 
    std::vector<DataType> supportedTypes =
    {
        DataType::BFloat16,
        DataType::Float16,
        DataType::Float32,
        DataType::QAsymmS8,
        DataType::QAsymmU8,
        DataType::QSymmS16
    };
 
    ValidateDataTypes(inputTensorInfo, supportedTypes, descriptorName);
    ValidateTensorDataTypesMatch(inputTensorInfo, outputTensorInfo, descriptorName, "input", "output");
}

References armnn::BFloat16, armnn::Float16, armnn::Float32, DataLayoutIndexed::GetChannelsIndex(), DataLayoutIndexed::GetHeightIndex(), TensorInfo::GetNumElements(), TensorInfo::GetShape(), DataLayoutIndexed::GetWidthIndex(), SpaceToBatchNdDescriptor::m_BlockShape, SpaceToBatchNdDescriptor::m_DataLayout, WorkloadInfo::m_InputTensorInfos, WorkloadInfo::m_OutputTensorInfos, SpaceToBatchNdDescriptor::m_PadList, QueueDescriptorWithParameters< SpaceToBatchNdDescriptor >::m_Parameters, armnn::QAsymmS8, armnn::QAsymmU8, armnn::QSymmS16, and QueueDescriptor::ValidateTensorNumDimensions().

---

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

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