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

Definition at line 75 of file ConvLayer.h.

Public Types
using	AlgorithmBackward_t = typename Architecture_t::AlgorithmBackward_t
using	AlgorithmDataType_t = typename Architecture_t::AlgorithmDataType_t
using	AlgorithmForward_t = typename Architecture_t::AlgorithmForward_t
using	AlgorithmHelper_t = typename Architecture_t::AlgorithmHelper_t
using	HelperDescriptor_t = typename Architecture_t::ActivationDescriptor_t
using	LayerDescriptor_t = typename Architecture_t::ConvolutionDescriptor_t
using	Matrix_t = typename Architecture_t::Matrix_t
using	ReduceTensorDescriptor_t = typename Architecture_t::ReduceTensorDescriptor_t
using	Scalar_t = typename Architecture_t::Scalar_t
using	Tensor_t = typename Architecture_t::Tensor_t
using	WeightsDescriptor_t = typename Architecture_t::FilterDescriptor_t

Public Member Functions
	TConvLayer (const TConvLayer &)
	Copy constructor.
	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.
	TConvLayer (TConvLayer< Architecture_t > *layer)
	Copy the conv layer provided as a pointer.
virtual	~TConvLayer ()
	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 applyDropout=false) override
	Computes activation of the layer for the given input.
EActivationFunction	GetActivationFunction () const
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
TDescriptors *	GetDescriptors ()
const TDescriptors *	GetDescriptors () const
Scalar_t	GetDropoutProbability () const
virtual std::vector< Matrix_t >	GetExtraLayerParameters () const
size_t	GetFilterDepth () const
	Getters.
size_t	GetFilterHeight () const
size_t	GetFilterWidth () const
Tensor_t &	GetForwardMatrices ()
const Tensor_t &	GetForwardMatrices () const
size_t	GetHeight () const
EInitialization	GetInitialization () const
Tensor_t &	GetInputActivation ()
const Tensor_t &	GetInputActivation () const
Matrix_t &	GetInputActivationAt (size_t i)
const Matrix_t &	GetInputActivationAt (size_t i) const
size_t	GetInputDepth () const
size_t	GetInputHeight () const
size_t	GetInputWidth () const
size_t	GetNLocalViewPixels () const
size_t	GetNLocalViews () const
Tensor_t &	GetOutput ()
const Tensor_t &	GetOutput () const
Matrix_t	GetOutputAt (size_t i)
const Matrix_t &	GetOutputAt (size_t i) const
size_t	GetPaddingHeight () const
size_t	GetPaddingWidth () const
ERegularization	GetRegularization () const
size_t	GetStrideCols () const
size_t	GetStrideRows () const
Scalar_t	GetWeightDecay () 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
TWorkspace *	GetWorkspace ()
const TWorkspace *	GetWorkspace () const
virtual void	Initialize ()
	Initialize the weights and biases according to the given initialization method.
bool	IsTraining () const
void	Print () const override
	Prints the info about the layer.
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.
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

Static Public Member Functions
static size_t	calculateDimension (size_t imgDim, size_t fltDim, size_t padding, size_t stride)
static size_t	calculateNLocalViewPixels (size_t depth, size_t height, size_t width)
static size_t	calculateNLocalViews (size_t inputHeight, size_t filterHeight, size_t paddingHeight, size_t strideRows, size_t inputWidth, size_t filterWidth, size_t paddingWidth, size_t strideCols)

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.
TDescriptors *	fDescriptors = nullptr
	Keeps the convolution, activations and filter descriptors.
Scalar_t	fDropoutProbability
	Probability that an input is active.
size_t	fFilterDepth
	The depth of the filter.
size_t	fFilterHeight
	The height of the filter.
size_t	fFilterWidth
	The width of the filter.
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.
size_t	fNLocalViewPixels
	The number of pixels in one local image view.
size_t	fNLocalViews
	The number of local views in one image.
Tensor_t	fOutput
	Activations of this layer.
size_t	fStrideCols
	The number of column pixels to slid the filter each step.
size_t	fStrideRows
	The number of row pixels to slid the filter each step.
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.
TWorkspace *	fWorkspace = nullptr

Private Member Functions
void	FreeWorkspace ()
void	InitializeDescriptors ()
void	InitializeWorkspace ()
void	ReleaseDescriptors ()

Private Attributes
std::vector< int >	fBackwardIndices
	Vector of indices used for a fast Im2Col in backward pass.
EActivationFunction	fF
	Activation function of the layer.
Tensor_t	fForwardTensor
	Cache tensor used for speeding-up the forward pass.
Tensor_t	fInputActivation
	First output of this layer after conv, before activation.
size_t	fPaddingHeight
	The number of zero layers added top and bottom of the input.
size_t	fPaddingWidth
	The number of zero layers left and right of the input.
ERegularization	fReg
	The regularization method.
Scalar_t	fWeightDecay
	The weight decay.

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

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

Member Typedef Documentation

◆ AlgorithmBackward_t

template<typename Architecture_t>

using TMVA::DNN::CNN::TConvLayer< Architecture_t >::AlgorithmBackward_t = typename Architecture_t::AlgorithmBackward_t

Definition at line 86 of file ConvLayer.h.

◆ AlgorithmDataType_t

template<typename Architecture_t>

using TMVA::DNN::CNN::TConvLayer< Architecture_t >::AlgorithmDataType_t = typename Architecture_t::AlgorithmDataType_t

Definition at line 91 of file ConvLayer.h.

◆ AlgorithmForward_t

template<typename Architecture_t>

using TMVA::DNN::CNN::TConvLayer< Architecture_t >::AlgorithmForward_t = typename Architecture_t::AlgorithmForward_t

Definition at line 85 of file ConvLayer.h.

◆ AlgorithmHelper_t

template<typename Architecture_t>

using TMVA::DNN::CNN::TConvLayer< Architecture_t >::AlgorithmHelper_t = typename Architecture_t::AlgorithmHelper_t

Definition at line 87 of file ConvLayer.h.

◆ HelperDescriptor_t

template<typename Architecture_t>

using TMVA::DNN::CNN::TConvLayer< Architecture_t >::HelperDescriptor_t = typename Architecture_t::ActivationDescriptor_t

Definition at line 83 of file ConvLayer.h.

◆ LayerDescriptor_t

template<typename Architecture_t>

using TMVA::DNN::CNN::TConvLayer< Architecture_t >::LayerDescriptor_t = typename Architecture_t::ConvolutionDescriptor_t

Definition at line 81 of file ConvLayer.h.

◆ Matrix_t

template<typename Architecture_t>

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

Definition at line 78 of file ConvLayer.h.

◆ ReduceTensorDescriptor_t

template<typename Architecture_t>

using TMVA::DNN::CNN::TConvLayer< Architecture_t >::ReduceTensorDescriptor_t = typename Architecture_t::ReduceTensorDescriptor_t

Definition at line 88 of file ConvLayer.h.

◆ Scalar_t

template<typename Architecture_t>

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

Definition at line 79 of file ConvLayer.h.

◆ Tensor_t

template<typename Architecture_t>

using TMVA::DNN::CNN::TConvLayer< Architecture_t >::Tensor_t = typename Architecture_t::Tensor_t

Definition at line 77 of file ConvLayer.h.

◆ WeightsDescriptor_t

template<typename Architecture_t>

using TMVA::DNN::CNN::TConvLayer< Architecture_t >::WeightsDescriptor_t = typename Architecture_t::FilterDescriptor_t

Definition at line 82 of file ConvLayer.h.

Constructor & Destructor Documentation

◆ TConvLayer() [1/3]

template<typename Architecture_t>

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

Definition at line 222 of file ConvLayer.h.

◆ TConvLayer() [2/3]

template<typename Architecture_t>

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

Copy the conv layer provided as a pointer.

Definition at line 257 of file ConvLayer.h.

◆ TConvLayer() [3/3]

template<typename Architecture_t>

TMVA::DNN::CNN::TConvLayer< Architecture_t >::TConvLayer ( const TConvLayer< Architecture_t > & convLayer )

Copy constructor.

Definition at line 276 of file ConvLayer.h.

◆ ~TConvLayer()

template<typename Architecture_t>

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

virtual

Destructor.

Definition at line 294 of file ConvLayer.h.

Member Function Documentation

◆ AddWeightsXMLTo()

template<typename Architecture_t>

void TMVA::DNN::CNN::TConvLayer< 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 369 of file ConvLayer.h.

◆ Backward()

template<typename Architecture_t>

auto TMVA::DNN::CNN::TConvLayer< 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 at the corresponding call to Forward(...).

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

Definition at line 326 of file ConvLayer.h.

◆ calculateDimension()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::calculateDimension	(	size_t	imgDim,
		size_t	fltDim,
		size_t	padding,
		size_t	stride )

static

Definition at line 402 of file ConvLayer.h.

◆ calculateNLocalViewPixels()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::calculateNLocalViewPixels	(	size_t	depth,
		size_t	height,
		size_t	width )

inlinestatic

Definition at line 97 of file ConvLayer.h.

◆ calculateNLocalViews()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::calculateNLocalViews	(	size_t	inputHeight,
		size_t	filterHeight,
		size_t	paddingHeight,
		size_t	strideRows,
		size_t	inputWidth,
		size_t	filterWidth,
		size_t	paddingWidth,
		size_t	strideCols )

static

Definition at line 413 of file ConvLayer.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::CNN::TConvLayer< Architecture_t >::Forward	(	Tensor_t &	input,
		bool	applyDropout = false )

overridevirtual

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. 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 311 of file ConvLayer.h.

◆ FreeWorkspace()

template<typename Architecture_t>

void TMVA::DNN::CNN::TConvLayer< Architecture_t >::FreeWorkspace ( )

private

Definition at line 445 of file ConvLayer.h.

◆ GetActivationFunction()

template<typename Architecture_t>

EActivationFunction TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetActivationFunction ( ) const

inline

Definition at line 204 of file ConvLayer.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.

◆ 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.

◆ GetDescriptors() [1/2]

template<typename Architecture_t>

TDescriptors * TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetDescriptors ( )

inline

Definition at line 209 of file ConvLayer.h.

◆ GetDescriptors() [2/2]

template<typename Architecture_t>

const TDescriptors * TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetDescriptors ( ) const

inline

Definition at line 210 of file ConvLayer.h.

◆ GetDropoutProbability()

template<typename Architecture_t>

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

inline

Definition at line 193 of file ConvLayer.h.

◆ GetExtraLayerParameters()

template<typename Architecture_t>

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

inlinevirtualinherited

Reimplemented in TMVA::DNN::TBatchNormLayer< Architecture_t >, TMVA::DNN::TBatchNormLayer< TCpu< AReal > >, and TMVA::DNN::TBatchNormLayer< TCuda< AReal > >.

Definition at line 210 of file GeneralLayer.h.

◆ GetFilterDepth()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetFilterDepth ( ) const

inline

Getters.

Definition at line 180 of file ConvLayer.h.

◆ GetFilterHeight()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetFilterHeight ( ) const

inline

Definition at line 181 of file ConvLayer.h.

◆ GetFilterWidth()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetFilterWidth ( ) const

inline

Definition at line 182 of file ConvLayer.h.

◆ GetForwardMatrices() [1/2]

template<typename Architecture_t>

Tensor_t & TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetForwardMatrices ( )

inline

Definition at line 202 of file ConvLayer.h.

◆ GetForwardMatrices() [2/2]

template<typename Architecture_t>

const Tensor_t & TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetForwardMatrices ( ) const

inline

Definition at line 201 of file ConvLayer.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.

◆ GetInputActivation() [1/2]

template<typename Architecture_t>

Tensor_t & TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetInputActivation ( )

inline

Definition at line 196 of file ConvLayer.h.

◆ GetInputActivation() [2/2]

template<typename Architecture_t>

const Tensor_t & TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetInputActivation ( ) const

inline

Definition at line 195 of file ConvLayer.h.

◆ GetInputActivationAt() [1/2]

template<typename Architecture_t>

Matrix_t & TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetInputActivationAt ( size_t i )

inline

Definition at line 198 of file ConvLayer.h.

◆ GetInputActivationAt() [2/2]

template<typename Architecture_t>

const Matrix_t & TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetInputActivationAt ( size_t i ) const

inline

Definition at line 199 of file ConvLayer.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.

◆ GetNLocalViewPixels()

template<typename Architecture_t>

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

inline

Definition at line 190 of file ConvLayer.h.

◆ GetNLocalViews()

template<typename Architecture_t>

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

inline

Definition at line 191 of file ConvLayer.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.

◆ GetPaddingHeight()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetPaddingHeight ( ) const

inline

Definition at line 187 of file ConvLayer.h.

◆ GetPaddingWidth()

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetPaddingWidth ( ) const

inline

Definition at line 188 of file ConvLayer.h.

◆ GetRegularization()

template<typename Architecture_t>

ERegularization TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetRegularization ( ) const

inline

Definition at line 205 of file ConvLayer.h.

◆ GetStrideCols()

template<typename Architecture_t>

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

inline

Definition at line 185 of file ConvLayer.h.

◆ GetStrideRows()

template<typename Architecture_t>

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

inline

Definition at line 184 of file ConvLayer.h.

◆ GetWeightDecay()

template<typename Architecture_t>

Scalar_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetWeightDecay ( ) const

inline

Definition at line 206 of file ConvLayer.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.

◆ GetWorkspace() [1/2]

template<typename Architecture_t>

TWorkspace * TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetWorkspace ( )

inline

Definition at line 212 of file ConvLayer.h.

◆ GetWorkspace() [2/2]

template<typename Architecture_t>

const TWorkspace * TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetWorkspace ( ) const

inline

Definition at line 213 of file ConvLayer.h.

◆ Initialize()

template<typename Architecture_t>

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

virtualinherited

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

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

Definition at line 395 of file GeneralLayer.h.

◆ InitializeDescriptors()

template<typename Architecture_t>

void TMVA::DNN::CNN::TConvLayer< Architecture_t >::InitializeDescriptors ( )

private

Definition at line 425 of file ConvLayer.h.

◆ InitializeWorkspace()

template<typename Architecture_t>

void TMVA::DNN::CNN::TConvLayer< Architecture_t >::InitializeWorkspace ( )

private

Definition at line 436 of file ConvLayer.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>

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

overridevirtual

Prints the info about the layer.

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

Definition at line 347 of file ConvLayer.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::CNN::TConvLayer< 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 393 of file ConvLayer.h.

◆ ReleaseDescriptors()

template<typename Architecture_t>

void TMVA::DNN::CNN::TConvLayer< Architecture_t >::ReleaseDescriptors ( )

private

Definition at line 430 of file ConvLayer.h.

◆ ResetTraining()

template<typename Architecture_t>

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

inlinevirtualinherited

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 >, TMVA::DNN::TBatchNormLayer< TCpu< AReal > >, and TMVA::DNN::TBatchNormLayer< TCuda< AReal > >.

Definition at line 121 of file GeneralLayer.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>

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

inlinevirtualinherited

Reimplemented in TMVA::DNN::TBatchNormLayer< Architecture_t >, TMVA::DNN::TBatchNormLayer< TCpu< AReal > >, and TMVA::DNN::TBatchNormLayer< TCuda< AReal > >.

Definition at line 212 of file GeneralLayer.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.

◆ fBackwardIndices

template<typename Architecture_t>

std::vector<int> TMVA::DNN::CNN::TConvLayer< Architecture_t >::fBackwardIndices

private

Vector of indices used for a fast Im2Col in backward pass.

Definition at line 125 of file ConvLayer.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.

◆ fDescriptors

template<typename Architecture_t>

TDescriptors* TMVA::DNN::CNN::TConvLayer< Architecture_t >::fDescriptors = nullptr

protected

Keeps the convolution, activations and filter descriptors.

Definition at line 116 of file ConvLayer.h.

◆ fDropoutProbability

template<typename Architecture_t>

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

protected

Probability that an input is active.

Definition at line 114 of file ConvLayer.h.

◆ fF

template<typename Architecture_t>

EActivationFunction TMVA::DNN::CNN::TConvLayer< Architecture_t >::fF

private

Activation function of the layer.

Definition at line 127 of file ConvLayer.h.

◆ fFilterDepth

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fFilterDepth

protected

The depth of the filter.

Definition at line 104 of file ConvLayer.h.

◆ fFilterHeight

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fFilterHeight

protected

The height of the filter.

Definition at line 105 of file ConvLayer.h.

◆ fFilterWidth

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fFilterWidth

protected

The width of the filter.

Definition at line 106 of file ConvLayer.h.

◆ fForwardTensor

template<typename Architecture_t>

Tensor_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fForwardTensor

private

Cache tensor used for speeding-up the forward pass.

Definition at line 131 of file ConvLayer.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.

◆ fInputActivation

template<typename Architecture_t>

Tensor_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fInputActivation

private

First output of this layer after conv, before activation.

Definition at line 123 of file ConvLayer.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.

◆ fNLocalViewPixels

template<typename Architecture_t>

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

protected

The number of pixels in one local image view.

Definition at line 111 of file ConvLayer.h.

◆ fNLocalViews

template<typename Architecture_t>

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

protected

The number of local views in one image.

Definition at line 112 of file ConvLayer.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.

◆ fPaddingHeight

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fPaddingHeight

private

The number of zero layers added top and bottom of the input.

Definition at line 120 of file ConvLayer.h.

◆ fPaddingWidth

template<typename Architecture_t>

size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fPaddingWidth

private

The number of zero layers left and right of the input.

Definition at line 121 of file ConvLayer.h.

◆ fReg

template<typename Architecture_t>

ERegularization TMVA::DNN::CNN::TConvLayer< Architecture_t >::fReg

private

The regularization method.

Definition at line 128 of file ConvLayer.h.

◆ fStrideCols

template<typename Architecture_t>

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

protected

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

Definition at line 109 of file ConvLayer.h.

◆ fStrideRows

template<typename Architecture_t>

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

protected

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

Definition at line 108 of file ConvLayer.h.

◆ fWeightDecay

template<typename Architecture_t>

Scalar_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fWeightDecay

private

The weight decay.

Definition at line 129 of file ConvLayer.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.

◆ fWorkspace

template<typename Architecture_t>

TWorkspace* TMVA::DNN::CNN::TConvLayer< Architecture_t >::fWorkspace = nullptr

protected

Definition at line 118 of file ConvLayer.h.

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

tmva/tmva/inc/TMVA/DNN/CNN/ConvLayer.h

Public Types

Public Member Functions

Static Public Member Functions

Protected Attributes

Private Member Functions

Private Attributes

Member Typedef Documentation

◆ AlgorithmBackward_t

◆ AlgorithmDataType_t

◆ AlgorithmForward_t

◆ AlgorithmHelper_t

◆ HelperDescriptor_t

◆ LayerDescriptor_t

◆ Matrix_t

◆ ReduceTensorDescriptor_t

◆ Scalar_t

◆ Tensor_t

◆ WeightsDescriptor_t

Constructor & Destructor Documentation

◆ TConvLayer() [1/3]

◆ TConvLayer() [2/3]

◆ TConvLayer() [3/3]

◆ ~TConvLayer()

Member Function Documentation

◆ AddWeightsXMLTo()

◆ Backward()

◆ calculateDimension()

◆ calculateNLocalViewPixels()

◆ calculateNLocalViews()

◆ CopyBiases()

◆ CopyParameters()

◆ CopyWeights()

◆ Forward()

◆ FreeWorkspace()

◆ GetActivationFunction()

◆ 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()

◆ GetDescriptors() [1/2]

◆ GetDescriptors() [2/2]

◆ GetDropoutProbability()

◆ GetExtraLayerParameters()

◆ GetFilterDepth()

◆ GetFilterHeight()

◆ GetFilterWidth()

◆ GetForwardMatrices() [1/2]

◆ GetForwardMatrices() [2/2]

◆ GetHeight()

◆ GetInitialization()

◆ GetInputActivation() [1/2]

◆ GetInputActivation() [2/2]

◆ GetInputActivationAt() [1/2]

◆ GetInputActivationAt() [2/2]

◆ GetInputDepth()

◆ GetInputHeight()

◆ GetInputWidth()

◆ GetNLocalViewPixels()

◆ GetNLocalViews()

◆ GetOutput() [1/2]

◆ GetOutput() [2/2]

◆ GetOutputAt() [1/2]

◆ GetOutputAt() [2/2]

◆ GetPaddingHeight()

◆ GetPaddingWidth()

◆ GetRegularization()

◆ GetStrideCols()

◆ GetStrideRows()

◆ GetWeightDecay()

◆ GetWeightGradients() [1/2]