SpaceToBatchNdQueueDescriptor Struct Reference

#include <WorkloadData.hpp>

Inheritance diagram for SpaceToBatchNdQueueDescriptor:

Public Member Functions
void	Validate (const WorkloadInfo &workloadInfo) const
Public Member Functions inherited from QueueDescriptor
void	ValidateInputsOutputs (const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) 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
Protected Member Functions inherited from QueueDescriptorWithParameters< SpaceToBatchNdDescriptor >
	~QueueDescriptorWithParameters ()=default
	QueueDescriptorWithParameters ()=default
	QueueDescriptorWithParameters (QueueDescriptorWithParameters const &)=default
QueueDescriptorWithParameters &	operator= (QueueDescriptorWithParameters const &)=default
Protected Member Functions inherited from QueueDescriptor
	~QueueDescriptor ()=default
	QueueDescriptor ()=default
	QueueDescriptor (QueueDescriptor const &)=default
QueueDescriptor &	operator= (QueueDescriptor const &)=default

Detailed Description

Definition at line 343 of file WorkloadData.hpp.

Member Function Documentation

Validate()

void Validate

(

const WorkloadInfo &

workloadInfo

)

const

Definition at line 1636 of file WorkloadData.cpp.

References armnn::BFloat16, armnn::Float16, armnn::Float32, DataLayoutIndexed::GetChannelsIndex(), DataLayoutIndexed::GetHeightIndex(), TensorInfo::GetNumElements(), TensorInfo::GetShape(), DataLayoutIndexed::GetWidthIndex(), WorkloadInfo::m_InputTensorInfos, WorkloadInfo::m_OutputTensorInfos, armnn::QAsymmS8, armnn::QAsymmU8, and armnn::QSymmS16.

{
    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");
}

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

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