template<typename Architecture_t>
class TMVA::DNN::VGeneralLayer< Architecture_t >

Generic General Layer class.

This class represents the general class for all layers in the Deep Learning Module.

Definition at line 51 of file GeneralLayer.h.

Public Member Functions
	VGeneralLayer (const VGeneralLayer &)
	Copy Constructor.

	VGeneralLayer (size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Depth, size_t Height, size_t Width, size_t WeightsNSlices, size_t WeightsNRows, size_t WeightsNCols, size_t BiasesNSlices, size_t BiasesNRows, size_t BiasesNCols, size_t OutputNSlices, size_t OutputNRows, size_t OutputNCols, EInitialization Init)
	Constructor.

	VGeneralLayer (size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Depth, size_t Height, size_t Width, size_t WeightsNSlices, std::vector< size_t > WeightsNRows, std::vector< size_t > WeightsNCols, size_t BiasesNSlices, std::vector< size_t > BiasesNRows, std::vector< size_t > BiasesNCols, size_t OutputNSlices, size_t OutputNRows, size_t OutputNCols, EInitialization Init)
	General Constructor with different weights dimension.

	VGeneralLayer (VGeneralLayer< Architecture_t > *layer)
	Copy the layer provided as a pointer.

virtual	~VGeneralLayer ()
	Virtual Destructor.

virtual void	AddWeightsXMLTo (void *parent)=0
	Writes the information and the weights about the layer in an XML node.

virtual void	Backward (Tensor_t &gradients_backward, const Tensor_t &activations_backward)=0
	Backpropagates the error.

void	CopyBiases (const std::vector< Matrix_t > &otherBiases)
	Copies the biases provided as an input.

template<typename Arch >
void	CopyParameters (const VGeneralLayer< Arch > &layer)
	Copy all trainable weight and biases from another equivalent layer but with different architecture The function can copy also extra parameters in addition to weights and biases if they are return by the function GetExtraLayerParameters.

void	CopyWeights (const std::vector< Matrix_t > &otherWeights)
	Copies the weights provided as an input.

virtual void	Forward (Tensor_t &input, bool applyDropout=false)=0
	Computes activation of the layer for the given input.

Tensor_t &	GetActivationGradients ()

const Tensor_t &	GetActivationGradients () const

Matrix_t	GetActivationGradientsAt (size_t i)

const Matrix_t &	GetActivationGradientsAt (size_t i) const

size_t	GetBatchSize () const
	Getters.

std::vector< Matrix_t > &	GetBiases ()

const std::vector< Matrix_t > &	GetBiases () const

Matrix_t &	GetBiasesAt (size_t i)

const Matrix_t &	GetBiasesAt (size_t i) const

std::vector< Matrix_t > &	GetBiasGradients ()

const std::vector< Matrix_t > &	GetBiasGradients () const

Matrix_t &	GetBiasGradientsAt (size_t i)

const Matrix_t &	GetBiasGradientsAt (size_t i) const

size_t	GetDepth () const

virtual std::vector< Matrix_t >	GetExtraLayerParameters () const

size_t	GetHeight () const

EInitialization	GetInitialization () const

size_t	GetInputDepth () const

size_t	GetInputHeight () const

size_t	GetInputWidth () const

Tensor_t &	GetOutput ()

const Tensor_t &	GetOutput () const

Matrix_t	GetOutputAt (size_t i)

const Matrix_t &	GetOutputAt (size_t i) const

std::vector< Matrix_t > &	GetWeightGradients ()

const std::vector< Matrix_t > &	GetWeightGradients () const

Matrix_t &	GetWeightGradientsAt (size_t i)

const Matrix_t &	GetWeightGradientsAt (size_t i) const

std::vector< Matrix_t > &	GetWeights ()

const std::vector< Matrix_t > &	GetWeights () const

Matrix_t &	GetWeightsAt (size_t i)

const Matrix_t &	GetWeightsAt (size_t i) const

size_t	GetWidth () const

virtual void	Initialize ()
	Initialize the weights and biases according to the given initialization method.

bool	IsTraining () const

virtual void	Print () const =0
	Prints the info about the layer.

void	ReadMatrixXML (void node, const char name, Matrix_t &matrix)

virtual void	ReadWeightsFromXML (void *parent)=0
	Read the information and the weights about the layer from XML node.

virtual void	ResetTraining ()
	Reset some training flags after a loop on all batches Some layer (e.g.

void	SetBatchSize (size_t batchSize)
	Setters.

void	SetDepth (size_t depth)

virtual void	SetDropoutProbability (Scalar_t)
	Set Dropout probability.

virtual void	SetExtraLayerParameters (const std::vector< Matrix_t > &)

void	SetHeight (size_t height)

void	SetInputDepth (size_t inputDepth)

void	SetInputHeight (size_t inputHeight)

void	SetInputWidth (size_t inputWidth)

void	SetIsTraining (bool isTraining)

void	SetWidth (size_t width)

void	Update (const Scalar_t learningRate)
	Updates the weights and biases, given the learning rate.

void	UpdateBiases (const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)
	Updates the biases, given the gradients and the learning rate.

void	UpdateBiasGradients (const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)
	Updates the bias gradients, given some other weight gradients and learning rate.

void	UpdateWeightGradients (const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)
	Updates the weight gradients, given some other weight gradients and learning rate.

void	UpdateWeights (const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)
	Updates the weights, given the gradients and the learning rate,.

void	WriteMatrixToXML (void node, const char name, const Matrix_t &matrix)

void	WriteTensorToXML (void node, const char name, const std::vector< Matrix_t > &tensor)
	helper functions for XML

Protected Attributes
Tensor_t	fActivationGradients
	Gradients w.r.t. the activations of this layer.

size_t	fBatchSize
	Batch size used for training and evaluation.

std::vector< Matrix_t >	fBiases
	The biases associated to the layer.

std::vector< Matrix_t >	fBiasGradients
	Gradients w.r.t. the bias values of the layer.

size_t	fDepth
	The depth of the layer.

size_t	fHeight
	The height of the layer.

EInitialization	fInit
	The initialization method.

size_t	fInputDepth
	The depth of the previous layer or input.

size_t	fInputHeight
	The height of the previous layer or input.

size_t	fInputWidth
	The width of the previous layer or input.

bool	fIsTraining
	Flag indicating the mode.

Tensor_t	fOutput
	Activations of this layer.

std::vector< Matrix_t >	fWeightGradients
	Gradients w.r.t. the weights of the layer.

std::vector< Matrix_t >	fWeights
	The weights associated to the layer.

size_t	fWidth
	The width of this layer.

Private Types
using	Matrix_t = typename Architecture_t::Matrix_t

using	Scalar_t = typename Architecture_t::Scalar_t

using	Tensor_t = typename Architecture_t::Tensor_t

#include <TMVA/DNN/GeneralLayer.h>

Inheritance diagram for TMVA::DNN::VGeneralLayer< Architecture_t >:

[legend]

Member Typedef Documentation

◆ Matrix_t

template<typename Architecture_t >

using TMVA::DNN::VGeneralLayer< Architecture_t >::Matrix_t = typename Architecture_t::Matrix_t

private

Definition at line 54 of file GeneralLayer.h.

◆ Scalar_t

template<typename Architecture_t >

using TMVA::DNN::VGeneralLayer< Architecture_t >::Scalar_t = typename Architecture_t::Scalar_t

private

Definition at line 55 of file GeneralLayer.h.

◆ Tensor_t

template<typename Architecture_t >

using TMVA::DNN::VGeneralLayer< Architecture_t >::Tensor_t = typename Architecture_t::Tensor_t

private

Definition at line 53 of file GeneralLayer.h.

Constructor & Destructor Documentation

◆ VGeneralLayer() [1/4]

template<typename Architecture_t >

TMVA::DNN::VGeneralLayer< Architecture_t >::VGeneralLayer	(	size_t	BatchSize,
		size_t	InputDepth,
		size_t	InputHeight,
		size_t	InputWidth,
		size_t	Depth,
		size_t	Height,
		size_t	Width,
		size_t	WeightsNSlices,
		size_t	WeightsNRows,
		size_t	WeightsNCols,
		size_t	BiasesNSlices,
		size_t	BiasesNRows,
		size_t	BiasesNCols,
		size_t	OutputNSlices,
		size_t	OutputNRows,
		size_t	OutputNCols,
		EInitialization	Init
	)

Constructor.

Definition at line 239 of file GeneralLayer.h.

◆ VGeneralLayer() [2/4]

template<typename Architecture_t >

TMVA::DNN::VGeneralLayer< Architecture_t >::VGeneralLayer	(	size_t	BatchSize,
		size_t	InputDepth,
		size_t	InputHeight,
		size_t	InputWidth,
		size_t	Depth,
		size_t	Height,
		size_t	Width,
		size_t	WeightsNSlices,
		std::vector< size_t >	WeightsNRows,
		std::vector< size_t >	WeightsNCols,
		size_t	BiasesNSlices,
		std::vector< size_t >	BiasesNRows,
		std::vector< size_t >	BiasesNCols,
		size_t	OutputNSlices,
		size_t	OutputNRows,
		size_t	OutputNCols,
		EInitialization	Init
	)

General Constructor with different weights dimension.

Definition at line 264 of file GeneralLayer.h.

◆ VGeneralLayer() [3/4]

template<typename Architecture_t >

TMVA::DNN::VGeneralLayer< Architecture_t >::VGeneralLayer ( VGeneralLayer< Architecture_t > * layer )

Copy the layer provided as a pointer.

Definition at line 295 of file GeneralLayer.h.

◆ VGeneralLayer() [4/4]

template<typename Architecture_t >

TMVA::DNN::VGeneralLayer< Architecture_t >::VGeneralLayer ( const VGeneralLayer< Architecture_t > & layer )

Copy Constructor.

Definition at line 336 of file GeneralLayer.h.

◆ ~VGeneralLayer()

template<typename Architecture_t >

TMVA::DNN::VGeneralLayer< Architecture_t >::~VGeneralLayer

virtual

Virtual Destructor.

Definition at line 388 of file GeneralLayer.h.

Member Function Documentation

◆ AddWeightsXMLTo()

template<typename Architecture_t >

virtual void TMVA::DNN::VGeneralLayer< Architecture_t >::AddWeightsXMLTo ( void * parent )

pure virtual

Writes the information and the weights about the layer in an XML node.

Implemented in TMVA::DNN::TBatchNormLayer< Architecture_t >, TMVA::DNN::CNN::TConvLayer< Architecture_t >, TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >, TMVA::DNN::TDenseLayer< Architecture_t >, TMVA::DNN::TReshapeLayer< Architecture_t >, TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >, TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >, and TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >.

◆ Backward()

template<typename Architecture_t >

virtual void TMVA::DNN::VGeneralLayer< Architecture_t >::Backward	(	Tensor_t &	gradients_backward,
		const Tensor_t &	activations_backward
	)

pure virtual

Backpropagates the error.

Must only be called directly at the corresponding call to Forward(...).

Implemented in TMVA::DNN::TBatchNormLayer< Architecture_t >, TMVA::DNN::CNN::TConvLayer< Architecture_t >, TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >, TMVA::DNN::TDenseLayer< Architecture_t >, TMVA::DNN::TReshapeLayer< Architecture_t >, TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >, TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >, and TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >.

◆ CopyBiases()

template<typename Architecture_t >

auto TMVA::DNN::VGeneralLayer< Architecture_t >::CopyBiases ( const std::vector< Matrix_t > & otherBiases )

Copies the biases provided as an input.

Definition at line 468 of file GeneralLayer.h.

◆ CopyParameters()

template<typename Architecture_t >

template<typename Arch >

void TMVA::DNN::VGeneralLayer< Architecture_t >::CopyParameters ( const VGeneralLayer< Arch > & layer )

Copy all trainable weight and biases from another equivalent layer but with different architecture The function can copy also extra parameters in addition to weights and biases if they are return by the function GetExtraLayerParameters.

Definition at line 478 of file GeneralLayer.h.

◆ CopyWeights()

template<typename Architecture_t >

auto TMVA::DNN::VGeneralLayer< Architecture_t >::CopyWeights ( const std::vector< Matrix_t > & otherWeights )

Copies the weights provided as an input.

Definition at line 458 of file GeneralLayer.h.

◆ Forward()

template<typename Architecture_t >

virtual void TMVA::DNN::VGeneralLayer< Architecture_t >::Forward	(	Tensor_t &	input,
		bool	applyDropout = `false`
	)

pure virtual

Computes activation of the layer for the given input.

The input must be in 3D tensor form with the different matrices corresponding to different events in the batch.

Implemented in TMVA::DNN::CNN::TConvLayer< Architecture_t >, TMVA::DNN::TDenseLayer< Architecture_t >, TMVA::DNN::TReshapeLayer< Architecture_t >, TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >, TMVA::DNN::TBatchNormLayer< Architecture_t >, TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >, TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >, and TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >.

◆ GetActivationGradients() [1/2]

template<typename Architecture_t >

Tensor_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetActivationGradients ( )

inline

Definition at line 200 of file GeneralLayer.h.

◆ GetActivationGradients() [2/2]

template<typename Architecture_t >

const Tensor_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetActivationGradients ( ) const

inline

Definition at line 199 of file GeneralLayer.h.

◆ GetActivationGradientsAt() [1/2]

template<typename Architecture_t >

Matrix_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetActivationGradientsAt ( size_t i )

inline

Definition at line 205 of file GeneralLayer.h.

◆ GetActivationGradientsAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetActivationGradientsAt ( size_t i ) const

inline

Definition at line 206 of file GeneralLayer.h.

◆ GetBatchSize()

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetBatchSize ( ) const

inline

Getters.

Definition at line 163 of file GeneralLayer.h.

◆ GetBiases() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiases ( )

inline

Definition at line 179 of file GeneralLayer.h.

◆ GetBiases() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiases ( ) const

inline

Definition at line 178 of file GeneralLayer.h.

◆ GetBiasesAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiasesAt ( size_t i )

inline

Definition at line 182 of file GeneralLayer.h.

◆ GetBiasesAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiasesAt ( size_t i ) const

inline

Definition at line 181 of file GeneralLayer.h.

◆ GetBiasGradients() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiasGradients ( )

inline

Definition at line 191 of file GeneralLayer.h.

◆ GetBiasGradients() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiasGradients ( ) const

inline

Definition at line 190 of file GeneralLayer.h.

◆ GetBiasGradientsAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiasGradientsAt ( size_t i )

inline

Definition at line 194 of file GeneralLayer.h.

◆ GetBiasGradientsAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetBiasGradientsAt ( size_t i ) const

inline

Definition at line 193 of file GeneralLayer.h.

◆ GetDepth()

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetDepth ( ) const

inline

Definition at line 167 of file GeneralLayer.h.

◆ GetExtraLayerParameters()

template<typename Architecture_t >

virtual std::vector< Matrix_t > TMVA::DNN::VGeneralLayer< Architecture_t >::GetExtraLayerParameters ( ) const

inlinevirtual

Reimplemented in TMVA::DNN::TBatchNormLayer< Architecture_t >.

Definition at line 210 of file GeneralLayer.h.

◆ GetHeight()

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetHeight ( ) const

inline

Definition at line 168 of file GeneralLayer.h.

◆ GetInitialization()

template<typename Architecture_t >

EInitialization TMVA::DNN::VGeneralLayer< Architecture_t >::GetInitialization ( ) const

inline

Definition at line 214 of file GeneralLayer.h.

◆ GetInputDepth()

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetInputDepth ( ) const

inline

Definition at line 164 of file GeneralLayer.h.

◆ GetInputHeight()

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetInputHeight ( ) const

inline

Definition at line 165 of file GeneralLayer.h.

◆ GetInputWidth()

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetInputWidth ( ) const

inline

Definition at line 166 of file GeneralLayer.h.

◆ GetOutput() [1/2]

template<typename Architecture_t >

Tensor_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetOutput ( )

inline

Definition at line 197 of file GeneralLayer.h.

◆ GetOutput() [2/2]

template<typename Architecture_t >

const Tensor_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetOutput ( ) const

inline

Definition at line 196 of file GeneralLayer.h.

◆ GetOutputAt() [1/2]

template<typename Architecture_t >

Matrix_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetOutputAt ( size_t i )

inline

Definition at line 202 of file GeneralLayer.h.

◆ GetOutputAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetOutputAt ( size_t i ) const

inline

Definition at line 203 of file GeneralLayer.h.

◆ GetWeightGradients() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeightGradients ( )

inline

Definition at line 185 of file GeneralLayer.h.

◆ GetWeightGradients() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeightGradients ( ) const

inline

Definition at line 184 of file GeneralLayer.h.

◆ GetWeightGradientsAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeightGradientsAt ( size_t i )

inline

Definition at line 188 of file GeneralLayer.h.

◆ GetWeightGradientsAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeightGradientsAt ( size_t i ) const

inline

Definition at line 187 of file GeneralLayer.h.

◆ GetWeights() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeights ( )

inline

Definition at line 173 of file GeneralLayer.h.

◆ GetWeights() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeights ( ) const

inline

Definition at line 172 of file GeneralLayer.h.

◆ GetWeightsAt() [1/2]

template<typename Architecture_t >

Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeightsAt ( size_t i )

inline

Definition at line 176 of file GeneralLayer.h.

◆ GetWeightsAt() [2/2]

template<typename Architecture_t >

const Matrix_t & TMVA::DNN::VGeneralLayer< Architecture_t >::GetWeightsAt ( size_t i ) const

inline

Definition at line 175 of file GeneralLayer.h.

◆ GetWidth()

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::GetWidth ( ) const

inline

Definition at line 169 of file GeneralLayer.h.

◆ Initialize()

template<typename Architecture_t >

auto TMVA::DNN::VGeneralLayer< Architecture_t >::Initialize

virtual

Initialize the weights and biases according to the given initialization method.

Reimplemented in TMVA::DNN::TBatchNormLayer< Architecture_t >, TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >, TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >, and TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >.

Definition at line 395 of file GeneralLayer.h.

◆ IsTraining()

template<typename Architecture_t >

bool TMVA::DNN::VGeneralLayer< Architecture_t >::IsTraining ( ) const

inline

Definition at line 170 of file GeneralLayer.h.

◆ Print()

template<typename Architecture_t >

virtual void TMVA::DNN::VGeneralLayer< Architecture_t >::Print ( ) const

pure virtual

Prints the info about the layer.

Implemented in TMVA::DNN::TBatchNormLayer< Architecture_t >, TMVA::DNN::CNN::TConvLayer< Architecture_t >, TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >, TMVA::DNN::TDenseLayer< Architecture_t >, TMVA::DNN::TReshapeLayer< Architecture_t >, TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >, TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >, and TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >.

◆ ReadMatrixXML()

template<typename Architecture_t >

auto TMVA::DNN::VGeneralLayer< Architecture_t >::ReadMatrixXML	(	void *	node,
		const char *	name,
		Matrix_t &	matrix
	)

Definition at line 544 of file GeneralLayer.h.

◆ ReadWeightsFromXML()

template<typename Architecture_t >

virtual void TMVA::DNN::VGeneralLayer< Architecture_t >::ReadWeightsFromXML ( void * parent )

pure virtual

Read the information and the weights about the layer from XML node.

Implemented in TMVA::DNN::TBatchNormLayer< Architecture_t >, TMVA::DNN::CNN::TConvLayer< Architecture_t >, TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >, TMVA::DNN::TDenseLayer< Architecture_t >, TMVA::DNN::TReshapeLayer< Architecture_t >, TMVA::DNN::RNN::TBasicGRULayer< Architecture_t >, TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t >, and TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t >.

◆ ResetTraining()

template<typename Architecture_t >

virtual void TMVA::DNN::VGeneralLayer< Architecture_t >::ResetTraining ( )

inlinevirtual

Reset some training flags after a loop on all batches Some layer (e.g.

batchnormalization) might need to implement the function in case some operations are needed after looping an all batches

Reimplemented in TMVA::DNN::TBatchNormLayer< Architecture_t >.

Definition at line 121 of file GeneralLayer.h.

◆ SetBatchSize()

template<typename Architecture_t >

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetBatchSize ( size_t batchSize )

inline

Setters.

Definition at line 217 of file GeneralLayer.h.

◆ SetDepth()

template<typename Architecture_t >

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetDepth ( size_t depth )

inline

Definition at line 221 of file GeneralLayer.h.

◆ SetDropoutProbability()

template<typename Architecture_t >

virtual void TMVA::DNN::VGeneralLayer< Architecture_t >::SetDropoutProbability ( Scalar_t )

inlinevirtual

Set Dropout probability.

Reimplemented for layesrs supporting droput

Reimplemented in TMVA::DNN::TDenseLayer< Architecture_t >.

Definition at line 160 of file GeneralLayer.h.

◆ SetExtraLayerParameters()

template<typename Architecture_t >

virtual void TMVA::DNN::VGeneralLayer< Architecture_t >::SetExtraLayerParameters ( const std::vector< Matrix_t > & )

inlinevirtual

Reimplemented in TMVA::DNN::TBatchNormLayer< Architecture_t >.

Definition at line 212 of file GeneralLayer.h.

◆ SetHeight()

template<typename Architecture_t >

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetHeight ( size_t height )

inline

Definition at line 222 of file GeneralLayer.h.

◆ SetInputDepth()

template<typename Architecture_t >

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetInputDepth ( size_t inputDepth )

inline

Definition at line 218 of file GeneralLayer.h.

◆ SetInputHeight()

template<typename Architecture_t >

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetInputHeight ( size_t inputHeight )

inline

Definition at line 219 of file GeneralLayer.h.

◆ SetInputWidth()

template<typename Architecture_t >

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetInputWidth ( size_t inputWidth )

inline

Definition at line 220 of file GeneralLayer.h.

◆ SetIsTraining()

template<typename Architecture_t >

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetIsTraining ( bool isTraining )

inline

Definition at line 224 of file GeneralLayer.h.

◆ SetWidth()

template<typename Architecture_t >

void TMVA::DNN::VGeneralLayer< Architecture_t >::SetWidth ( size_t width )

inline

Definition at line 223 of file GeneralLayer.h.

◆ Update()

template<typename Architecture_t >

auto TMVA::DNN::VGeneralLayer< Architecture_t >::Update ( const Scalar_t learningRate )

Updates the weights and biases, given the learning rate.

Definition at line 410 of file GeneralLayer.h.

◆ UpdateBiases()

template<typename Architecture_t >

auto TMVA::DNN::VGeneralLayer< Architecture_t >::UpdateBiases	(	const std::vector< Matrix_t > &	biasGradients,
		const Scalar_t	learningRate
	)

Updates the biases, given the gradients and the learning rate.

Definition at line 428 of file GeneralLayer.h.

◆ UpdateBiasGradients()

template<typename Architecture_t >

auto TMVA::DNN::VGeneralLayer< Architecture_t >::UpdateBiasGradients	(	const std::vector< Matrix_t > &	biasGradients,
		const Scalar_t	learningRate
	)

Updates the bias gradients, given some other weight gradients and learning rate.

Definition at line 448 of file GeneralLayer.h.

◆ UpdateWeightGradients()

template<typename Architecture_t >

auto TMVA::DNN::VGeneralLayer< Architecture_t >::UpdateWeightGradients	(	const std::vector< Matrix_t > &	weightGradients,
		const Scalar_t	learningRate
	)

Updates the weight gradients, given some other weight gradients and learning rate.

Definition at line 438 of file GeneralLayer.h.

◆ UpdateWeights()

template<typename Architecture_t >

auto TMVA::DNN::VGeneralLayer< Architecture_t >::UpdateWeights	(	const std::vector< Matrix_t > &	weightGradients,
		const Scalar_t	learningRate
	)

Updates the weights, given the gradients and the learning rate,.

Definition at line 418 of file GeneralLayer.h.

◆ WriteMatrixToXML()

template<typename Architecture_t >

auto TMVA::DNN::VGeneralLayer< Architecture_t >::WriteMatrixToXML	(	void *	node,
		const char *	name,
		const Matrix_t &	matrix
	)

Definition at line 521 of file GeneralLayer.h.

◆ WriteTensorToXML()

template<typename Architecture_t >

auto TMVA::DNN::VGeneralLayer< Architecture_t >::WriteTensorToXML	(	void *	node,
		const char *	name,
		const std::vector< Matrix_t > &	tensor
	)

helper functions for XML

Definition at line 496 of file GeneralLayer.h.

Member Data Documentation

◆ fActivationGradients

template<typename Architecture_t >

Tensor_t TMVA::DNN::VGeneralLayer< Architecture_t >::fActivationGradients

protected

Gradients w.r.t. the activations of this layer.

Definition at line 78 of file GeneralLayer.h.

◆ fBatchSize

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fBatchSize

protected

Batch size used for training and evaluation.

Definition at line 59 of file GeneralLayer.h.

◆ fBiases

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::VGeneralLayer< Architecture_t >::fBiases

protected

The biases associated to the layer.

Definition at line 72 of file GeneralLayer.h.

◆ fBiasGradients

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::VGeneralLayer< Architecture_t >::fBiasGradients

protected

Gradients w.r.t. the bias values of the layer.

Definition at line 75 of file GeneralLayer.h.

◆ fDepth

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fDepth

protected

The depth of the layer.

Definition at line 65 of file GeneralLayer.h.

◆ fHeight

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fHeight

protected

The height of the layer.

Definition at line 66 of file GeneralLayer.h.

◆ fInit

template<typename Architecture_t >

EInitialization TMVA::DNN::VGeneralLayer< Architecture_t >::fInit

protected

The initialization method.

Definition at line 80 of file GeneralLayer.h.

◆ fInputDepth

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fInputDepth

protected

The depth of the previous layer or input.

Definition at line 61 of file GeneralLayer.h.

◆ fInputHeight

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fInputHeight

protected

The height of the previous layer or input.

Definition at line 62 of file GeneralLayer.h.

◆ fInputWidth

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fInputWidth

protected

The width of the previous layer or input.

Definition at line 63 of file GeneralLayer.h.

◆ fIsTraining

template<typename Architecture_t >

bool TMVA::DNN::VGeneralLayer< Architecture_t >::fIsTraining

protected

Flag indicating the mode.

Definition at line 69 of file GeneralLayer.h.

◆ fOutput

template<typename Architecture_t >

Tensor_t TMVA::DNN::VGeneralLayer< Architecture_t >::fOutput

protected

Activations of this layer.

Definition at line 77 of file GeneralLayer.h.

◆ fWeightGradients

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::VGeneralLayer< Architecture_t >::fWeightGradients

protected

Gradients w.r.t. the weights of the layer.

Definition at line 74 of file GeneralLayer.h.

◆ fWeights

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::VGeneralLayer< Architecture_t >::fWeights

protected

The weights associated to the layer.

Definition at line 71 of file GeneralLayer.h.

◆ fWidth

template<typename Architecture_t >

size_t TMVA::DNN::VGeneralLayer< Architecture_t >::fWidth

protected

The width of this layer.

Definition at line 67 of file GeneralLayer.h.

tmva/tmva/inc/TMVA/DNN/GeneralLayer.h

Public Member Functions

Protected Attributes

Private Types

Member Typedef Documentation

◆ Matrix_t

◆ Scalar_t

◆ Tensor_t

Constructor & Destructor Documentation

◆ VGeneralLayer() [1/4]

◆ VGeneralLayer() [2/4]

◆ VGeneralLayer() [3/4]

◆ VGeneralLayer() [4/4]

◆ ~VGeneralLayer()

Member Function Documentation

◆ AddWeightsXMLTo()

◆ Backward()

◆ CopyBiases()

◆ CopyParameters()

◆ CopyWeights()

◆ Forward()

◆ GetActivationGradients() [1/2]

◆ GetActivationGradients() [2/2]

◆ GetActivationGradientsAt() [1/2]

◆ GetActivationGradientsAt() [2/2]

◆ GetBatchSize()

◆ GetBiases() [1/2]

◆ GetBiases() [2/2]

◆ GetBiasesAt() [1/2]

◆ GetBiasesAt() [2/2]

◆ GetBiasGradients() [1/2]

◆ GetBiasGradients() [2/2]

◆ GetBiasGradientsAt() [1/2]

◆ GetBiasGradientsAt() [2/2]

◆ GetDepth()

◆ GetExtraLayerParameters()

◆ GetHeight()

◆ GetInitialization()

◆ GetInputDepth()

◆ GetInputHeight()

◆ GetInputWidth()

◆ GetOutput() [1/2]

◆ GetOutput() [2/2]

◆ GetOutputAt() [1/2]

◆ GetOutputAt() [2/2]

◆ GetWeightGradients() [1/2]

◆ GetWeightGradients() [2/2]

◆ GetWeightGradientsAt() [1/2]

◆ GetWeightGradientsAt() [2/2]

◆ GetWeights() [1/2]

◆ GetWeights() [2/2]

◆ GetWeightsAt() [1/2]

◆ GetWeightsAt() [2/2]

◆ GetWidth()

◆ Initialize()

◆ IsTraining()

◆ Print()

◆ ReadMatrixXML()

◆ ReadWeightsFromXML()

◆ ResetTraining()

◆ SetBatchSize()

◆ SetDepth()

◆ SetDropoutProbability()

◆ SetExtraLayerParameters()

◆ SetHeight()

◆ SetInputDepth()

◆ SetInputHeight()

◆ SetInputWidth()

◆ SetIsTraining()

◆ SetWidth()

◆ Update()

◆ UpdateBiases()

◆ UpdateBiasGradients()

◆ UpdateWeightGradients()

◆ UpdateWeights()

◆ WriteMatrixToXML()

◆ WriteTensorToXML()

Member Data Documentation

◆ fActivationGradients

◆ fBatchSize

◆ fBiases