template<typename Architecture_t>
class TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >

Generic Max Pooling Layer class.

This generic Max Pooling Layer Class represents a pooling layer of a CNN. It inherits all of the properties of the convolutional layer TConvLayer, but it overrides the propagation methods. In a sense, max pooling can be seen as non-linear convolution: a filter slides over the input and produces one element as a function of the the elements within the receptive field. In addition to that, it contains a matrix of winning units.

The height and width of the weights and biases is set to 0, since this layer does not contain any weights.

Definition at line 57 of file MaxPoolLayer.h.

Public Types
using	Matrix_t = typename Architecture_t::Matrix_t

using	Scalar_t = typename Architecture_t::Scalar_t

Public Types inherited from TMVA::DNN::CNN::TConvLayer< Architecture_t >
using	Matrix_t = typename Architecture_t::Matrix_t

using	Scalar_t = typename Architecture_t::Scalar_t

Public Member Functions
	TMaxPoolLayer (const TMaxPoolLayer &)
	Copy constructor. More...

	TMaxPoolLayer (size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t FilterHeight, size_t FilterWidth, size_t StrideRows, size_t StrideCols, Scalar_t DropoutProbability)
	Constructor. More...

	TMaxPoolLayer (TMaxPoolLayer< Architecture_t > *layer)
	Copy the max pooling layer provided as a pointer. More...

	~TMaxPoolLayer ()
	Destructor. More...

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

void	Backward (std::vector< Matrix_t > &gradients_backward, const std::vector< Matrix_t > &activations_backward, std::vector< Matrix_t > &inp1, std::vector< Matrix_t > &inp2)
	Depending on the winning units determined during the Forward pass, it only forwards the derivatives to the right units in the previous layer. More...

void	Forward (std::vector< Matrix_t > &input, bool applyDropout=false)
	Computes activation of the layer for the given input. More...

std::vector< Matrix_t > &	GetIndexMatrix ()

const std::vector< Matrix_t > &	GetIndexMatrix () const
	Getters. More...

void	Print () const
	Prints the info about the layer. More...

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

Public Member Functions inherited from TMVA::DNN::CNN::TConvLayer< Architecture_t >
	TConvLayer (const TConvLayer &)
	Copy constructor. More...

	TConvLayer (size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Depth, EInitialization Init, size_t FilterHeight, size_t FilterWidth, size_t StrideRows, size_t StrideCols, size_t PaddingHeight, size_t PaddingWidth, Scalar_t DropoutProbability, EActivationFunction f, ERegularization Reg, Scalar_t WeightDecay)
	Constructor. More...

	TConvLayer (TConvLayer< Architecture_t > *layer)
	Copy the conv layer provided as a pointer. More...

	~TConvLayer ()
	Destructor. More...

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

void	Backward (std::vector< Matrix_t > &gradients_backward, const std::vector< Matrix_t > &activations_backward, std::vector< Matrix_t > &inp1, std::vector< Matrix_t > &inp2)
	Compute weight, bias and activation gradients. More...

void	Forward (std::vector< Matrix_t > &input, bool applyDropout=false)
	Computes activation of the layer for the given input. More...

EActivationFunction	GetActivationFunction () const

std::vector< Matrix_t > &	GetDerivatives ()

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

Matrix_t &	GetDerivativesAt (size_t i)

const Matrix_t &	GetDerivativesAt (size_t i) const

Scalar_t	GetDropoutProbability () const

size_t	GetFilterDepth () const
	Getters. More...

size_t	GetFilterHeight () const

size_t	GetFilterWidth () const

std::vector< Matrix_t > &	GetForwardMatrices ()

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

size_t	GetNLocalViewPixels () const

size_t	GetNLocalViews () const

size_t	GetPaddingHeight () const

size_t	GetPaddingWidth () const

ERegularization	GetRegularization () const

size_t	GetStrideCols () const

size_t	GetStrideRows () const

Scalar_t	GetWeightDecay () const

void	Print () const
	Prints the info about the layer. More...

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

Public Member Functions inherited from TMVA::DNN::VGeneralLayer< Architecture_t >
	VGeneralLayer (const VGeneralLayer &)
	Copy Constructor. More...

	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. More...

	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. More...

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

virtual	~VGeneralLayer ()
	Virtual Destructor. More...

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

virtual void	Backward (std::vector< Matrix_t > &gradients_backward, const std::vector< Matrix_t > &activations_backward, std::vector< Matrix_t > &inp1, std::vector< Matrix_t > &inp2)=0
	Backpropagates the error. More...

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

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

virtual void	Forward (std::vector< Matrix_t > &input, bool applyDropout=false)=0
	Computes activation of the layer for the given input. More...

std::vector< Matrix_t > &	GetActivationGradients ()

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

Matrix_t &	GetActivationGradientsAt (size_t i)

const Matrix_t &	GetActivationGradientsAt (size_t i) const

size_t	GetBatchSize () const
	Getters. More...

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

size_t	GetHeight () const

EInitialization	GetInitialization () const

size_t	GetInputDepth () const

size_t	GetInputHeight () const

size_t	GetInputWidth () const

std::vector< Matrix_t > &	GetOutput ()

const std::vector< Matrix_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

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

bool	IsTraining () const

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

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. More...

void	SetBatchSize (size_t batchSize)
	Setters. More...

void	SetDepth (size_t depth)

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. More...

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

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

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

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

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 More...

Private Attributes
std::vector< Matrix_t >	indexMatrix
	Matrix of indices for the backward pass. More...

Additional Inherited Members
Protected Attributes inherited from TMVA::DNN::CNN::TConvLayer< Architecture_t >
Scalar_t	fDropoutProbability
	Probability that an input is active. More...

size_t	fFilterDepth
	The depth of the filter. More...

size_t	fFilterHeight
	The height of the filter. More...

size_t	fFilterWidth
	The width of the filter. More...

size_t	fNLocalViewPixels
	The number of pixels in one local image view. More...

size_t	fNLocalViews
	The number of local views in one image. More...

size_t	fStrideCols
	The number of column pixels to slid the filter each step. More...

size_t	fStrideRows
	The number of row pixels to slid the filter each step. More...

Protected Attributes inherited from TMVA::DNN::VGeneralLayer< Architecture_t >
std::vector< Matrix_t >	fActivationGradients
	Gradients w.r.t. the activations of this layer. More...

size_t	fBatchSize
	Batch size used for training and evaluation. More...

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

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

size_t	fDepth
	The depth of the layer. More...

size_t	fHeight
	The height of the layer. More...

EInitialization	fInit
	The initialization method. More...

size_t	fInputDepth
	The depth of the previous layer or input. More...

size_t	fInputHeight
	The height of the previous layer or input. More...

size_t	fInputWidth
	The width of the previous layer or input. More...

bool	fIsTraining
	Flag indicatig the mode. More...

std::vector< Matrix_t >	fOutput
	Activations of this layer. More...

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

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

size_t	fWidth
	The width of this layer. More...

#include <TMVA/DNN/CNN/MaxPoolLayer.h>

Inheritance diagram for TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >:

[legend]

Member Typedef Documentation

◆ Matrix_t

template<typename Architecture_t >

using TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::Matrix_t = typename Architecture_t::Matrix_t

Definition at line 60 of file MaxPoolLayer.h.

◆ Scalar_t

template<typename Architecture_t >

using TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::Scalar_t = typename Architecture_t::Scalar_t

Definition at line 61 of file MaxPoolLayer.h.

Constructor & Destructor Documentation

◆ TMaxPoolLayer() [1/3]

template<typename Architecture_t >

TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::TMaxPoolLayer	(	size_t	BatchSize,
		size_t	InputDepth,
		size_t	InputHeight,
		size_t	InputWidth,
		size_t	FilterHeight,
		size_t	FilterWidth,
		size_t	StrideRows,
		size_t	StrideCols,
		Scalar_t	DropoutProbability
	)

Constructor.

Definition at line 110 of file MaxPoolLayer.h.

◆ TMaxPoolLayer() [2/3]

template<typename Architecture_t >

TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::TMaxPoolLayer ( TMaxPoolLayer< Architecture_t > * layer )

Copy the max pooling layer provided as a pointer.

Definition at line 126 of file MaxPoolLayer.h.

◆ TMaxPoolLayer() [3/3]

template<typename Architecture_t >

TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::TMaxPoolLayer ( const TMaxPoolLayer< Architecture_t > & layer )

Copy constructor.

Definition at line 136 of file MaxPoolLayer.h.

◆ ~TMaxPoolLayer()

template<typename Architecture_t >

TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::~TMaxPoolLayer

Destructor.

Definition at line 146 of file MaxPoolLayer.h.

Member Function Documentation

◆ AddWeightsXMLTo()

template<typename Architecture_t >

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

virtual

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

Reimplemented from TMVA::DNN::CNN::TConvLayer< Architecture_t >.

Definition at line 202 of file MaxPoolLayer.h.

◆ Backward()

template<typename Architecture_t >

auto TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::Backward	(	std::vector< Matrix_t > &	gradients_backward,
		const std::vector< Matrix_t > &	activations_backward,
		std::vector< Matrix_t > &	inp1,
		std::vector< Matrix_t > &	inp2
	)

virtual

Depending on the winning units determined during the Forward pass, it only forwards the derivatives to the right units in the previous layer.

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

Reimplemented from TMVA::DNN::CNN::TConvLayer< Architecture_t >.

Definition at line 168 of file MaxPoolLayer.h.

◆ Forward()

template<typename Architecture_t >

auto TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::Forward	(	std::vector< Matrix_t > &	input,
		bool	applyDropout = `false`
	)

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. It spatially downsamples the input matrices.

Reimplemented from TMVA::DNN::CNN::TConvLayer< Architecture_t >.

Definition at line 152 of file MaxPoolLayer.h.

◆ GetIndexMatrix() [1/2]

template<typename Architecture_t >

std::vector< Matrix_t > & TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::GetIndexMatrix ( )

inline

Definition at line 104 of file MaxPoolLayer.h.

◆ GetIndexMatrix() [2/2]

template<typename Architecture_t >

const std::vector< Matrix_t > & TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::GetIndexMatrix ( ) const

inline

Getters.

Definition at line 103 of file MaxPoolLayer.h.

◆ Print()

template<typename Architecture_t >

auto TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::Print

virtual

Prints the info about the layer.

Reimplemented from TMVA::DNN::CNN::TConvLayer< Architecture_t >.

Definition at line 184 of file MaxPoolLayer.h.

◆ ReadWeightsFromXML()

template<typename Architecture_t >

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

virtual

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

Reimplemented from TMVA::DNN::CNN::TConvLayer< Architecture_t >.

Definition at line 216 of file MaxPoolLayer.h.

Member Data Documentation

◆ indexMatrix

template<typename Architecture_t >

std::vector<Matrix_t> TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::indexMatrix

private

Matrix of indices for the backward pass.

Definition at line 64 of file MaxPoolLayer.h.

Libraries for TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >:

[legend]

Public Types

Public Member Functions

Private Attributes

Additional Inherited Members

Member Typedef Documentation

◆ Matrix_t

◆ Scalar_t

Constructor & Destructor Documentation

◆ TMaxPoolLayer() [1/3]

◆ TMaxPoolLayer() [2/3]

◆ TMaxPoolLayer() [3/3]

◆ ~TMaxPoolLayer()

Member Function Documentation

◆ AddWeightsXMLTo()

◆ Backward()

◆ Forward()

◆ GetIndexMatrix() [1/2]

◆ GetIndexMatrix() [2/2]

◆ Print()

◆ ReadWeightsFromXML()

Member Data Documentation

◆ indexMatrix