template<typename T>
class TMVA::Experimental::SOFIE::ROperator_InstanceNormalization< T >

Implementation of the ONNX InstanceNormalization operator.

The input X has shape (N, C, D1, ..., Dn). For every sample n and channel c, the elements over the spatial dimensions D1, ..., Dn are normalized to zero mean and unit variance, and then scaled and shifted with the per-channel scale and B tensors, which both have shape (C):

Y[n, c, ...] = scale[c] * (X[n, c, ...] - mean[n, c]) / sqrt(var[n, c] + epsilon) + B[c]

Definition at line 26 of file ROperator_InstanceNormalization.hxx.

Public Member Functions
	ROperator_InstanceNormalization ()

	ROperator_InstanceNormalization (float epsilon, std::string nameInput, std::string nameScale, std::string nameBias, std::string nameOutput)

std::string	Generate (std::string) override

virtual std::string	GenerateDeclCode ()

virtual std::string	GenerateInitCode ()

virtual std::string	GenerateSessionMembersCode (std::string)

virtual std::vector< std::string >	GetBlasRoutines ()

std::span< const std::string_view >	GetOpInputTensors () const

std::span< const std::string_view >	GetOpOutputTensors () const

virtual std::vector< std::string >	GetStdLibs ()

virtual std::string	Header ()

void	Initialize (RModel &model) override

bool	IsOutputConstant () const
	check if the output of the operator is Constant and is evaluated at initialization time

std::vector< std::vector< size_t > >	ShapeInference (std::vector< std::vector< size_t > > inputShapes) override

virtual std::vector< ETensorType >	TypeInference (std::vector< ETensorType >)

Protected Attributes
std::vector< std::string_view >	fInputTensorNames

bool	fIsOutputConstant = false
	flag to identify if operator has a constant output (no need to generate code)

bool	fIsOutputParamShape = false
	flag to identify of the output represents a parametric shape (can be known at compile time)

std::vector< std::string_view >	fOutputTensorNames

bool	fUseSession = false
	flag to identify if using the session class

const std::string	SP = " "
	space used to correctly indent the generated C++ code

Private Attributes
float	fEpsilon

std::string	fNBias

std::string	fNInput

std::string	fNOutput

std::string	fNScale

std::vector< size_t >	fShape

std::string	fType

#include <TMVA/ROperator_InstanceNormalization.hxx>

Inheritance diagram for TMVA::Experimental::SOFIE::ROperator_InstanceNormalization< T >:

[legend]

Constructor & Destructor Documentation

◆ ROperator_InstanceNormalization() [1/2]

template<typename T >

TMVA::Experimental::SOFIE::ROperator_InstanceNormalization< T >::ROperator_InstanceNormalization ( )

inline

Definition at line 37 of file ROperator_InstanceNormalization.hxx.

◆ ROperator_InstanceNormalization() [2/2]

template<typename T >

TMVA::Experimental::SOFIE::ROperator_InstanceNormalization< T >::ROperator_InstanceNormalization	(	float	epsilon,
		std::string	nameInput,
		std::string	nameScale,
		std::string	nameBias,
		std::string	nameOutput )

inline

Definition at line 39 of file ROperator_InstanceNormalization.hxx.

Member Function Documentation

◆ Generate()

template<typename T >

std::string TMVA::Experimental::SOFIE::ROperator_InstanceNormalization< T >::Generate ( std::string )

inlineoverridevirtual

Implements TMVA::Experimental::SOFIE::ROperator.

Definition at line 85 of file ROperator_InstanceNormalization.hxx.

◆ GenerateDeclCode()

virtual std::string TMVA::Experimental::SOFIE::ROperator::GenerateDeclCode ( )

inlinevirtualinherited

Reimplemented in TMVA::Experimental::SOFIE::ROperator_Random.

Definition at line 31 of file ROperator.hxx.

◆ GenerateInitCode()

virtual std::string TMVA::Experimental::SOFIE::ROperator::GenerateInitCode ( )

inlinevirtualinherited

Definition at line 29 of file ROperator.hxx.

◆ GenerateSessionMembersCode()

virtual std::string TMVA::Experimental::SOFIE::ROperator::GenerateSessionMembersCode ( std::string )

inlinevirtualinherited

Reimplemented in TMVA::Experimental::SOFIE::ROperator_LSTM< T >, TMVA::Experimental::SOFIE::ROperator_Pool< T >, TMVA::Experimental::SOFIE::ROperator_RNN< T >, and TMVA::Experimental::SOFIE::ROperator_NonZero< T >.

Definition at line 33 of file ROperator.hxx.

◆ GetBlasRoutines()

virtual std::vector< std::string > TMVA::Experimental::SOFIE::ROperator::GetBlasRoutines ( )

inlinevirtualinherited

Reimplemented in TMVA::Experimental::SOFIE::ROperator_BatchNormalization< T >, TMVA::Experimental::SOFIE::ROperator_Conv< T >, TMVA::Experimental::SOFIE::ROperator_ConvTranspose< T >, TMVA::Experimental::SOFIE::ROperator_Einsum< T >, TMVA::Experimental::SOFIE::ROperator_Gemm< T >, TMVA::Experimental::SOFIE::ROperator_GRU< T >, TMVA::Experimental::SOFIE::ROperator_LayerNormalization< T >, TMVA::Experimental::SOFIE::ROperator_LSTM< T >, and TMVA::Experimental::SOFIE::ROperator_RNN< T >.

Definition at line 22 of file ROperator.hxx.

◆ GetOpInputTensors()

std::span< const std::string_view > TMVA::Experimental::SOFIE::ROperator::GetOpInputTensors ( ) const

inlineinherited

Definition at line 54 of file ROperator.hxx.

◆ GetOpOutputTensors()

std::span< const std::string_view > TMVA::Experimental::SOFIE::ROperator::GetOpOutputTensors ( ) const

inlineinherited

Definition at line 58 of file ROperator.hxx.

◆ GetStdLibs()

virtual std::vector< std::string > TMVA::Experimental::SOFIE::ROperator::GetStdLibs ( )

inlinevirtualinherited

Definition at line 23 of file ROperator.hxx.

◆ Header()

virtual std::string TMVA::Experimental::SOFIE::ROperator::Header ( )

inlinevirtualinherited

Definition at line 34 of file ROperator.hxx.

◆ Initialize()

template<typename T >

void TMVA::Experimental::SOFIE::ROperator_InstanceNormalization< T >::Initialize ( RModel & model )

inlineoverridevirtual

Implements TMVA::Experimental::SOFIE::ROperator.

Definition at line 56 of file ROperator_InstanceNormalization.hxx.

◆ IsOutputConstant()

bool TMVA::Experimental::SOFIE::ROperator::IsOutputConstant ( ) const

inlineinherited

check if the output of the operator is Constant and is evaluated at initialization time

Definition at line 37 of file ROperator.hxx.

◆ ShapeInference()

template<typename T >

std::vector< std::vector< size_t > > TMVA::Experimental::SOFIE::ROperator_InstanceNormalization< T >::ShapeInference ( std::vector< std::vector< size_t > > inputShapes )