#include <WorkloadData.hpp>

Inheritance diagram for FullyConnectedQueueDescriptor:

Public Member Functions
	FullyConnectedQueueDescriptor ()

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

template<typename T >
const T *	GetAdditionalInformation () const

Public Attributes
const ConstTensorHandle *	m_Weight

const ConstTensorHandle *	m_Bias

Public Attributes inherited from QueueDescriptorWithParameters< FullyConnectedDescriptor >
FullyConnectedDescriptor	m_Parameters

Public Attributes inherited from QueueDescriptor
std::vector< ITensorHandle * >	m_Inputs

std::vector< ITensorHandle * >	m_Outputs

void *	m_AdditionalInfoObject

Additional Inherited Members
Protected Member Functions inherited from QueueDescriptorWithParameters< FullyConnectedDescriptor >
	~QueueDescriptorWithParameters ()=default

	QueueDescriptorWithParameters ()=default

	QueueDescriptorWithParameters (QueueDescriptorWithParameters const &)=default

QueueDescriptorWithParameters &	operator= (QueueDescriptorWithParameters const &)=default

Protected Member Functions inherited from QueueDescriptor
	~QueueDescriptor ()=default

	QueueDescriptor ()

	QueueDescriptor (QueueDescriptor const &)=default

QueueDescriptor &	operator= (QueueDescriptor const &)=default

Detailed Description

Definition at line 170 of file WorkloadData.hpp.

Constructor & Destructor Documentation

◆ FullyConnectedQueueDescriptor()

FullyConnectedQueueDescriptor ( )

inline

Definition at line 172 of file WorkloadData.hpp.

         : m_Weight(nullptr)
         , m_Bias(nullptr)
     {
     }

Member Function Documentation

◆ Validate()

void Validate ( const WorkloadInfo & workloadInfo ) const

Definition at line 1047 of file WorkloadData.cpp.

References armnn::BFloat16, armnn::Float16, armnn::Float32, armnn::GetBiasDataType(), TensorInfo::GetDataType(), TensorInfo::GetNumDimensions(), WorkloadInfo::m_InputTensorInfos, WorkloadInfo::m_OutputTensorInfos, armnn::QAsymmS8, armnn::QAsymmU8, and armnn::QSymmS16.

 {
     const std::string descriptorName{"FullyConnectedQueueDescriptor"};
 
     uint32_t numInputs = 1;
     if (!m_Parameters.m_ConstantWeights)
     {
         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(outputTensorInfo, descriptorName, 2, "output");
 
     if (!(inputTensorInfo.GetNumDimensions() == 2 || inputTensorInfo.GetNumDimensions() == 4))
     {
         throw InvalidArgumentException(descriptorName + ": Input tensor must have 2 or 4 dimensions.");
     }
 
     TensorInfo weightTensorInfo;
     if (m_Parameters.m_ConstantWeights)
     {
         ValidatePointer(m_Weight, descriptorName, "weight");
         weightTensorInfo = m_Weight->GetTensorInfo();
     }
     else
     {
         weightTensorInfo  = workloadInfo.m_InputTensorInfos[1];
     }
     ValidateTensorNumDimensions(weightTensorInfo, descriptorName, 2, "weight");
 
     if (m_Parameters.m_BiasEnabled)
     {
         TensorInfo biasTensorInfo;
         if (m_Parameters.m_ConstantWeights)
         {
             ValidatePointer(m_Bias, descriptorName, "bias");
             biasTensorInfo = m_Bias->GetTensorInfo();
         }
         else
         {
             biasTensorInfo  = workloadInfo.m_InputTensorInfos[2];
         }
         // Validates type and quantization values.
         ValidateBiasTensorQuantization(biasTensorInfo, inputTensorInfo, weightTensorInfo, descriptorName);
         ValidateTensorDataType(biasTensorInfo, GetBiasDataType(inputTensorInfo.GetDataType()), descriptorName, "bias");
         ValidateTensorNumDimensions(biasTensorInfo, descriptorName, 1, "bias");
     }
 
     // Check the supported data types
     std::vector<DataType> supportedTypes =
     {
         DataType::BFloat16,
         DataType::Float32,
         DataType::Float16,
         DataType::QAsymmS8,
         DataType::QAsymmU8,
         DataType::QSymmS16
     };
 
     ValidateDataTypes(inputTensorInfo, supportedTypes, descriptorName);
 
     // For FullyConnected, 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");
     }
 }