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 generic virtual base class VGeneralLayer. 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 54 of file MaxPoolLayer.h.

Public Types
using	Matrix_t = typename Architecture_t::Matrix_t

using	Scalar_t = typename Architecture_t::Scalar_t

Public Member Functions
	TMaxPoolLayer (size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Height, size_t Width, size_t OutputNSlices, size_t OutputNRows, size_t OutputNCols, size_t FrameHeight, size_t FrameWidth, 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 (const TMaxPoolLayer &)
	Copy constructor. 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...

Scalar_t	GetDropoutProbability () const

size_t	GetFrameHeight () const

size_t	GetFrameWidth () const

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

std::vector< Matrix_t > &	GetIndexMatrix ()

size_t	GetNLocalViewPixels () const

size_t	GetNLocalViews () const

size_t	GetStrideCols () const

size_t	GetStrideRows () 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 (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...

	VGeneralLayer (const VGeneralLayer &)
	Copy Constructor. More...

virtual	~VGeneralLayer ()
	Virtual Destructor. 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...

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

std::vector< Matrix_t > &	GetActivationGradients ()

Matrix_t &	GetActivationGradientsAt (size_t i)

const Matrix_t &	GetActivationGradientsAt (size_t i) const

size_t	GetBatchSize () const
	Getters. More...

const 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)

size_t	GetDepth () const

size_t	GetHeight () const

EInitialization	GetInitialization () const

size_t	GetInputDepth () const

size_t	GetInputHeight () const

size_t	GetInputWidth () const

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

std::vector< Matrix_t > &	GetOutput ()

Matrix_t &	GetOutputAt (size_t i)

const Matrix_t &	GetOutputAt (size_t i) const

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)

size_t	GetWidth () const

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

bool	IsTraining () const

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

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
Scalar_t	fDropoutProbability
	Probability that an input is active. More...

size_t	fFrameHeight
	The height of the frame. More...

size_t	fFrameWidth
	The width of the frame. 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...

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

Additional Inherited Members
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 56 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 57 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	Height,
		size_t	Width,
		size_t	OutputNSlices,
		size_t	OutputNRows,
		size_t	OutputNCols,
		size_t	FrameHeight,
		size_t	FrameWidth,
		size_t	StrideRows,
		size_t	StrideCols,
		Scalar_t	DropoutProbability
	)

Constructor.

Definition at line 129 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 146 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 159 of file MaxPoolLayer.h.

◆ ~TMaxPoolLayer()

template<typename Architecture_t >

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

Destructor.

Definition at line 172 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.

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

Definition at line 223 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(...).

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

Definition at line 194 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.

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

Definition at line 178 of file MaxPoolLayer.h.

◆ GetDropoutProbability()

template<typename Architecture_t>

Scalar_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::GetDropoutProbability ( ) const

inline

Definition at line 124 of file MaxPoolLayer.h.

◆ GetFrameHeight()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::GetFrameHeight ( ) const

inline

Definition at line 115 of file MaxPoolLayer.h.

◆ GetFrameWidth()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::GetFrameWidth ( ) const

inline

Definition at line 116 of file MaxPoolLayer.h.

◆ GetIndexMatrix() [1/2]

template<typename Architecture_t>

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

inline

Getters.

Definition at line 112 of file MaxPoolLayer.h.

◆ GetIndexMatrix() [2/2]

template<typename Architecture_t>

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

inline

Definition at line 113 of file MaxPoolLayer.h.

◆ GetNLocalViewPixels()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::GetNLocalViewPixels ( ) const

inline

Definition at line 121 of file MaxPoolLayer.h.

◆ GetNLocalViews()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::GetNLocalViews ( ) const

inline

Definition at line 122 of file MaxPoolLayer.h.

◆ GetStrideCols()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::GetStrideCols ( ) const

inline

Definition at line 119 of file MaxPoolLayer.h.

◆ GetStrideRows()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::GetStrideRows ( ) const

inline

Definition at line 118 of file MaxPoolLayer.h.

◆ Print()

template<typename Architecture_t >

auto TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::Print ( ) const

virtual

Prints the info about the layer.

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

Definition at line 205 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.

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

Definition at line 237 of file MaxPoolLayer.h.

Member Data Documentation

◆ fDropoutProbability

template<typename Architecture_t>

Scalar_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::fDropoutProbability

private

Probability that an input is active.

Definition at line 71 of file MaxPoolLayer.h.

◆ fFrameHeight

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::fFrameHeight

private

The height of the frame.

Definition at line 62 of file MaxPoolLayer.h.

◆ fFrameWidth

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::fFrameWidth

private

The width of the frame.

Definition at line 63 of file MaxPoolLayer.h.

◆ fNLocalViewPixels

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::fNLocalViewPixels

private

The number of pixels in one local image view.

Definition at line 68 of file MaxPoolLayer.h.

◆ fNLocalViews

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::fNLocalViews

private

The number of local views in one image.

Definition at line 69 of file MaxPoolLayer.h.

◆ fStrideCols

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::fStrideCols

private

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

Definition at line 66 of file MaxPoolLayer.h.

◆ fStrideRows

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TMaxPoolLayer< Architecture_t >::fStrideRows

private

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

Definition at line 65 of file MaxPoolLayer.h.

◆ 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 60 of file MaxPoolLayer.h.

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

[legend]

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

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()

◆ GetDropoutProbability()

◆ GetFrameHeight()

◆ GetFrameWidth()

◆ GetIndexMatrix() [1/2]

◆ GetIndexMatrix() [2/2]

◆ GetNLocalViewPixels()

◆ GetNLocalViews()

◆ GetStrideCols()

◆ GetStrideRows()

◆ Print()

◆ ReadWeightsFromXML()

Member Data Documentation

◆ fDropoutProbability

◆ fFrameHeight

◆ fFrameWidth

◆ fNLocalViewPixels

◆ fNLocalViews

◆ fStrideCols

◆ fStrideRows

◆ indexMatrix

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