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

Layer implementing Batch Normalization.

The input from each batch are normalized during training to have zero mean and unit variance and they are then scaled by two parameter, different for each input variable:

a scale factor gamma
an offset beta

In addition a running batch mean and variance is computed and stored in the class During inference the inputs are not normalized using the batch mean but the previously computed at running mean and variance If momentum is in [0,1) the running mean and variances are the exponential averages using the momentum value running_mean = momentum * running_mean + (1-momentum) * batch_mean If instead momentum<1 the cumulative average is computed running_mean = (nb/(nb+1) * running_mean + 1/(nb+1) * batch_mean

See more at [https://arxiv.org/pdf/1502.03167v3.pdf]

Definition at line 64 of file BatchNormLayer.h.

Public Types
using	BNormDescriptors_t = typename Architecture_t::BNormDescriptors_t
using	HelperDescriptor_t = typename Architecture_t::TensorDescriptor_t
using	Matrix_t = typename Architecture_t::Matrix_t
using	Scalar_t = typename Architecture_t::Scalar_t
using	Tensor_t = typename Architecture_t::Tensor_t

Public Member Functions
	TBatchNormLayer (const TBatchNormLayer &)
	Copy Constructor.
	TBatchNormLayer (size_t batchSize, size_t inputDepth, size_t inputHeight, size_t inputWidth, const std::vector< size_t > &shape, int axis=-1, Scalar_t momentum=-1., Scalar_t epsilon=0.0001)
	Constructor.
	TBatchNormLayer (TBatchNormLayer< Architecture_t > *layer)
	Copy the dense layer provided as a pointer.
	~TBatchNormLayer ()
	Destructor.
void	AddWeightsXMLTo (void *parent) override
	Writes the information and the weights about the layer in an XML node.
void	Backward (Tensor_t &gradients_backward, const Tensor_t &activations_backward) override
	Compute weight, bias and activation gradients.
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.
void	Forward (Tensor_t &input, bool inTraining=true) override
	Compute 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
Matrix_t &	GetBatchMean ()
const Matrix_t &	GetBatchMean () 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
Scalar_t	GetEpsilon () const
std::vector< Matrix_t >	GetExtraLayerParameters () const override
size_t	GetHeight () const
EInitialization	GetInitialization () const
size_t	GetInputDepth () const
size_t	GetInputHeight () const
size_t	GetInputWidth () const
Matrix_t &	GetIVariance ()
const Matrix_t &	GetIVariance () const
Scalar_t	GetMomentum () const
Matrix_t &	GetMuVector ()
const Matrix_t &	GetMuVector () const
Scalar_t	GetNormAxis () const
int &	GetNTrainedBatches ()
const int &	GetNTrainedBatches () const
Tensor_t &	GetOutput ()
const Tensor_t &	GetOutput () const
Matrix_t	GetOutputAt (size_t i)
const Matrix_t &	GetOutputAt (size_t i) const
Matrix_t &	GetReshapedData ()
const Matrix_t &	GetReshapedData () const
Matrix_t &	GetVariance ()
const Matrix_t &	GetVariance () const
Matrix_t &	GetVarVector ()
const Matrix_t &	GetVarVector () 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
void	Initialize () override
	Initialize the weights and biases according to the given initialization method.
bool	IsTraining () const
void	Print () const override
	Printing the layer info.
void	ReadMatrixXML (void node, const char name, Matrix_t &matrix)
void	ReadWeightsFromXML (void *parent) override
	Read the information and the weights about the layer from XML node.
void	ResetTraining () override
	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.
void	SetExtraLayerParameters (const std::vector< Matrix_t > &params) override
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

Static Protected Member Functions
static size_t	CalculateNormDim (int axis, size_t c, size_t h, size_t w)

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 Attributes
Tensor_t	fDerivatives
	First fDerivatives of the activations of this layer.
TDescriptors *	fDescriptors = nullptr
Scalar_t	fEpsilon
Matrix_t	fIVar
Scalar_t	fMomentum
	The weight decay.
Matrix_t	fMu
Matrix_t	fMu_Training
int	fNormAxis
	Normalization axis. For each element of this axis we will compute mean and stddev.
Tensor_t	fReshapedData
int	fTrainedBatches = 0
Matrix_t	fVar
Matrix_t	fVar_Training

#include <TMVA/DNN/BatchNormLayer.h>

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

Member Typedef Documentation

◆ BNormDescriptors_t

template<typename Architecture_t>

using TMVA::DNN::TBatchNormLayer< Architecture_t >::BNormDescriptors_t = typename Architecture_t::BNormDescriptors_t

Definition at line 72 of file BatchNormLayer.h.

◆ HelperDescriptor_t

template<typename Architecture_t>

using TMVA::DNN::TBatchNormLayer< Architecture_t >::HelperDescriptor_t = typename Architecture_t::TensorDescriptor_t

Definition at line 71 of file BatchNormLayer.h.

◆ Matrix_t

template<typename Architecture_t>

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

Definition at line 68 of file BatchNormLayer.h.

◆ Scalar_t

template<typename Architecture_t>

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

Definition at line 67 of file BatchNormLayer.h.

◆ Tensor_t

template<typename Architecture_t>

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

Definition at line 69 of file BatchNormLayer.h.

Constructor & Destructor Documentation

◆ TBatchNormLayer() [1/3]

template<typename Architecture_t>

TMVA::DNN::TBatchNormLayer< Architecture_t >::TBatchNormLayer	(	size_t	batchSize,
		size_t	inputDepth,
		size_t	inputHeight,
		size_t	inputWidth,
		const std::vector< size_t > &	shape,
		int	axis = -1,
		Scalar_t	momentum = -1.,
		Scalar_t	epsilon = 0.0001 )

Constructor.

Definition at line 219 of file BatchNormLayer.h.

◆ TBatchNormLayer() [2/3]

template<typename Architecture_t>

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

Copy the dense layer provided as a pointer.

Definition at line 242 of file BatchNormLayer.h.

◆ TBatchNormLayer() [3/3]

template<typename Architecture_t>

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

Copy Constructor.

Definition at line 251 of file BatchNormLayer.h.

◆ ~TBatchNormLayer()

template<typename Architecture_t>

TMVA::DNN::TBatchNormLayer< Architecture_t >::~TBatchNormLayer ( )

Destructor.

Definition at line 259 of file BatchNormLayer.h.

Member Function Documentation

◆ AddWeightsXMLTo()

template<typename Architecture_t>

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

overridevirtual

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

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 387 of file BatchNormLayer.h.

◆ Backward()

template<typename Architecture_t>

auto TMVA::DNN::TBatchNormLayer< Architecture_t >::Backward	(	Tensor_t &	gradients_backward,
		const Tensor_t &	activations_backward )

overridevirtual

Compute weight, bias and activation gradients.

Uses the precomputed first partial derivatives of the activation function computed during forward propagation and modifies them. Must only be called directly a the corresponding call to Forward(...).

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 337 of file BatchNormLayer.h.

◆ CalculateNormDim()

template<typename Architecture_t>

size_t TMVA::DNN::TBatchNormLayer< Architecture_t >::CalculateNormDim	(	int	axis,
		size_t	c,
		size_t	h,
		size_t	w )

inlinestaticprotected

Definition at line 199 of file BatchNormLayer.h.

◆ CopyBiases()

template<typename Architecture_t>

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

inherited

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 )

inherited

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 )

inherited

Copies the weights provided as an input.

Definition at line 458 of file GeneralLayer.h.

◆ Forward()

template<typename Architecture_t>

auto TMVA::DNN::TBatchNormLayer< Architecture_t >::Forward	(	Tensor_t &	input,
		bool	inTraining = true )

overridevirtual

Compute 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. Computes activations as well as the first partial derivative of the activation function at those activations.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 295 of file BatchNormLayer.h.

◆ GetActivationGradients() [1/2]

template<typename Architecture_t>

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

inlineinherited

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

inlineinherited

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 )

inlineinherited

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

inlineinherited

Definition at line 206 of file GeneralLayer.h.

◆ GetBatchMean() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetBatchMean ( )

inline

Definition at line 149 of file BatchNormLayer.h.

◆ GetBatchMean() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetBatchMean ( ) const

inline

Definition at line 148 of file BatchNormLayer.h.

◆ GetBatchSize()

template<typename Architecture_t>

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

inlineinherited

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 ( )

inlineinherited

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

inlineinherited

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 )

inlineinherited

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

inlineinherited

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 ( )

inlineinherited

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

inlineinherited

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 )

inlineinherited

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

inlineinherited

Definition at line 193 of file GeneralLayer.h.

◆ GetDepth()

template<typename Architecture_t>

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

inlineinherited

Definition at line 167 of file GeneralLayer.h.

◆ GetEpsilon()

template<typename Architecture_t>

Scalar_t TMVA::DNN::TBatchNormLayer< Architecture_t >::GetEpsilon ( ) const

inline

Definition at line 177 of file BatchNormLayer.h.

◆ GetExtraLayerParameters()

template<typename Architecture_t>

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

inlineoverridevirtual

Reimplemented from TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 185 of file BatchNormLayer.h.

◆ GetHeight()

template<typename Architecture_t>

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

inlineinherited

Definition at line 168 of file GeneralLayer.h.

◆ GetInitialization()

template<typename Architecture_t>

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

inlineinherited

Definition at line 214 of file GeneralLayer.h.

◆ GetInputDepth()

template<typename Architecture_t>

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

inlineinherited

Definition at line 164 of file GeneralLayer.h.

◆ GetInputHeight()

template<typename Architecture_t>

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

inlineinherited

Definition at line 165 of file GeneralLayer.h.

◆ GetInputWidth()

template<typename Architecture_t>

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

inlineinherited

Definition at line 166 of file GeneralLayer.h.

◆ GetIVariance() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetIVariance ( )

inline

Definition at line 161 of file BatchNormLayer.h.

◆ GetIVariance() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetIVariance ( ) const

inline

Definition at line 160 of file BatchNormLayer.h.

◆ GetMomentum()

template<typename Architecture_t>

Scalar_t TMVA::DNN::TBatchNormLayer< Architecture_t >::GetMomentum ( ) const

inline

Definition at line 174 of file BatchNormLayer.h.

◆ GetMuVector() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetMuVector ( )

inline

Definition at line 165 of file BatchNormLayer.h.

◆ GetMuVector() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetMuVector ( ) const

inline

Definition at line 164 of file BatchNormLayer.h.

◆ GetNormAxis()

template<typename Architecture_t>

Scalar_t TMVA::DNN::TBatchNormLayer< Architecture_t >::GetNormAxis ( ) const

inline

Definition at line 180 of file BatchNormLayer.h.

◆ GetNTrainedBatches() [1/2]

template<typename Architecture_t>

int & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetNTrainedBatches ( )

inline

Definition at line 145 of file BatchNormLayer.h.

◆ GetNTrainedBatches() [2/2]

template<typename Architecture_t>

const int & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetNTrainedBatches ( ) const

inline

Definition at line 144 of file BatchNormLayer.h.

◆ GetOutput() [1/2]

template<typename Architecture_t>

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

inlineinherited

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

inlineinherited

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 )

inlineinherited

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

inlineinherited

Definition at line 203 of file GeneralLayer.h.

◆ GetReshapedData() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetReshapedData ( )

inline

Definition at line 183 of file BatchNormLayer.h.

◆ GetReshapedData() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetReshapedData ( ) const

inline

Definition at line 182 of file BatchNormLayer.h.

◆ GetVariance() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetVariance ( )

inline

Definition at line 157 of file BatchNormLayer.h.

◆ GetVariance() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetVariance ( ) const

inline

Definition at line 156 of file BatchNormLayer.h.

◆ GetVarVector() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetVarVector ( )

inline

Definition at line 169 of file BatchNormLayer.h.

◆ GetVarVector() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::TBatchNormLayer< Architecture_t >::GetVarVector ( ) const

inline

Definition at line 168 of file BatchNormLayer.h.

◆ GetWeightGradients() [1/2]

template<typename Architecture_t>

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

inlineinherited

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

inlineinherited

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 )

inlineinherited

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

inlineinherited

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 ( )

inlineinherited

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

inlineinherited

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 )

inlineinherited

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

inlineinherited

Definition at line 175 of file GeneralLayer.h.

◆ GetWidth()

template<typename Architecture_t>

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

inlineinherited

Definition at line 169 of file GeneralLayer.h.

◆ Initialize()

template<typename Architecture_t>

auto TMVA::DNN::TBatchNormLayer< Architecture_t >::Initialize ( )

overridevirtual

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

Reimplemented from TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 269 of file BatchNormLayer.h.

◆ IsTraining()

template<typename Architecture_t>

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

inlineinherited

Definition at line 170 of file GeneralLayer.h.

◆ Print()

template<typename Architecture_t>

void TMVA::DNN::TBatchNormLayer< Architecture_t >::Print ( ) const

overridevirtual

Printing the layer info.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 369 of file BatchNormLayer.h.

◆ ReadMatrixXML()

template<typename Architecture_t>

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

inherited

Definition at line 544 of file GeneralLayer.h.

◆ ReadWeightsFromXML()

template<typename Architecture_t>

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

overridevirtual

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

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 412 of file BatchNormLayer.h.

◆ ResetTraining()

template<typename Architecture_t>

void TMVA::DNN::TBatchNormLayer< Architecture_t >::ResetTraining ( )

inlineoverridevirtual

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 from TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 129 of file BatchNormLayer.h.

◆ SetBatchSize()

template<typename Architecture_t>

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

inlineinherited

Setters.

Definition at line 217 of file GeneralLayer.h.

◆ SetDepth()

template<typename Architecture_t>

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

inlineinherited

Definition at line 221 of file GeneralLayer.h.

◆ SetDropoutProbability()

template<typename Architecture_t>

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

inlinevirtualinherited

Set Dropout probability.

Reimplemented for layers supporting droput

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

Definition at line 160 of file GeneralLayer.h.

◆ SetExtraLayerParameters()

template<typename Architecture_t>

void TMVA::DNN::TBatchNormLayer< Architecture_t >::SetExtraLayerParameters ( const std::vector< Matrix_t > & params )

inlineoverridevirtual

Reimplemented from TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 192 of file BatchNormLayer.h.

◆ SetHeight()

template<typename Architecture_t>

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

inlineinherited

Definition at line 222 of file GeneralLayer.h.

◆ SetInputDepth()

template<typename Architecture_t>

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

inlineinherited

Definition at line 218 of file GeneralLayer.h.

◆ SetInputHeight()

template<typename Architecture_t>

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

inlineinherited

Definition at line 219 of file GeneralLayer.h.

◆ SetInputWidth()

template<typename Architecture_t>

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

inlineinherited

Definition at line 220 of file GeneralLayer.h.

◆ SetIsTraining()

template<typename Architecture_t>

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

inlineinherited

Definition at line 224 of file GeneralLayer.h.

◆ SetWidth()

template<typename Architecture_t>

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

inlineinherited

Definition at line 223 of file GeneralLayer.h.

◆ Update()

template<typename Architecture_t>

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

inherited

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 )

inherited

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 )

inherited

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 )

inherited

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 )

inherited

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 )

inherited

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 )

inherited

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

protectedinherited

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

protectedinherited

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

protectedinherited

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

protectedinherited

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

protectedinherited

The depth of the layer.

Definition at line 65 of file GeneralLayer.h.

◆ fDerivatives

template<typename Architecture_t>

Tensor_t TMVA::DNN::TBatchNormLayer< Architecture_t >::fDerivatives

private

First fDerivatives of the activations of this layer.

Definition at line 77 of file BatchNormLayer.h.

◆ fDescriptors

template<typename Architecture_t>

TDescriptors* TMVA::DNN::TBatchNormLayer< Architecture_t >::fDescriptors = nullptr

private

Definition at line 97 of file BatchNormLayer.h.

◆ fEpsilon

template<typename Architecture_t>

Scalar_t TMVA::DNN::TBatchNormLayer< Architecture_t >::fEpsilon

private

Definition at line 82 of file BatchNormLayer.h.

◆ fHeight

template<typename Architecture_t>

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

protectedinherited

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

protectedinherited

The initialization method.

Definition at line 80 of file GeneralLayer.h.

◆ fInputDepth

template<typename Architecture_t>

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

protectedinherited

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

protectedinherited

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

protectedinherited

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

protectedinherited

Flag indicating the mode.

Definition at line 69 of file GeneralLayer.h.

◆ fIVar

template<typename Architecture_t>

Matrix_t TMVA::DNN::TBatchNormLayer< Architecture_t >::fIVar

private

Definition at line 86 of file BatchNormLayer.h.

◆ fMomentum

template<typename Architecture_t>

Scalar_t TMVA::DNN::TBatchNormLayer< Architecture_t >::fMomentum

private

The weight decay.

Definition at line 81 of file BatchNormLayer.h.

◆ fMu

template<typename Architecture_t>

Matrix_t TMVA::DNN::TBatchNormLayer< Architecture_t >::fMu

private

Definition at line 84 of file BatchNormLayer.h.

◆ fMu_Training

template<typename Architecture_t>

Matrix_t TMVA::DNN::TBatchNormLayer< Architecture_t >::fMu_Training

private

Definition at line 88 of file BatchNormLayer.h.

◆ fNormAxis

template<typename Architecture_t>

int TMVA::DNN::TBatchNormLayer< Architecture_t >::fNormAxis

private

Normalization axis. For each element of this axis we will compute mean and stddev.

Definition at line 79 of file BatchNormLayer.h.

◆ fOutput

template<typename Architecture_t>

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

protectedinherited

Activations of this layer.

Definition at line 77 of file GeneralLayer.h.

◆ fReshapedData

template<typename Architecture_t>

Tensor_t TMVA::DNN::TBatchNormLayer< Architecture_t >::fReshapedData

private

Definition at line 92 of file BatchNormLayer.h.

◆ fTrainedBatches

template<typename Architecture_t>

int TMVA::DNN::TBatchNormLayer< Architecture_t >::fTrainedBatches = 0

private

Definition at line 95 of file BatchNormLayer.h.

◆ fVar

template<typename Architecture_t>

Matrix_t TMVA::DNN::TBatchNormLayer< Architecture_t >::fVar

private

Definition at line 85 of file BatchNormLayer.h.

◆ fVar_Training

template<typename Architecture_t>

Matrix_t TMVA::DNN::TBatchNormLayer< Architecture_t >::fVar_Training

private

Definition at line 89 of file BatchNormLayer.h.

◆ fWeightGradients

template<typename Architecture_t>

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

protectedinherited

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

protectedinherited

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

protectedinherited

The width of this layer.

Definition at line 67 of file GeneralLayer.h.

The documentation for this class was generated from the following file:

tmva/tmva/inc/TMVA/DNN/BatchNormLayer.h

Public Types

Public Member Functions

Static Protected Member Functions

Protected Attributes

Private Attributes

Member Typedef Documentation

◆ BNormDescriptors_t

◆ HelperDescriptor_t

◆ Matrix_t

◆ Scalar_t

◆ Tensor_t

Constructor & Destructor Documentation

◆ TBatchNormLayer() [1/3]

◆ TBatchNormLayer() [2/3]

◆ TBatchNormLayer() [3/3]

◆ ~TBatchNormLayer()

Member Function Documentation

◆ AddWeightsXMLTo()

◆ Backward()

◆ CalculateNormDim()

◆ CopyBiases()

◆ CopyParameters()

◆ CopyWeights()

◆ Forward()

◆ GetActivationGradients() [1/2]

◆ GetActivationGradients() [2/2]

◆ GetActivationGradientsAt() [1/2]

◆ GetActivationGradientsAt() [2/2]

◆ GetBatchMean() [1/2]

◆ GetBatchMean() [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()

◆ GetEpsilon()

◆ GetExtraLayerParameters()

◆ GetHeight()

◆ GetInitialization()

◆ GetInputDepth()

◆ GetInputHeight()

◆ GetInputWidth()

◆ GetIVariance() [1/2]

◆ GetIVariance() [2/2]

◆ GetMomentum()

◆ GetMuVector() [1/2]

◆ GetMuVector() [2/2]

◆ GetNormAxis()

◆ GetNTrainedBatches() [1/2]

◆ GetNTrainedBatches() [2/2]

◆ GetOutput() [1/2]

◆ GetOutput() [2/2]

◆ GetOutputAt() [1/2]

◆ GetOutputAt() [2/2]

◆ GetReshapedData() [1/2]

◆ GetReshapedData() [2/2]

◆ GetVariance() [1/2]

◆ GetVariance() [2/2]

◆ GetVarVector() [1/2]

◆ GetVarVector() [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()