#include <Dense.hpp>

Inheritance diagram for NNFS::Dense:

Public Member Functions
	Dense (int n_input, int n_output, double l1_weights_regularizer=.0, double l1_biases_regularizer=.0, double l2_weights_regularizer=.0, double l2_biases_regularizer=.0)
	Construct a new Dense object.

void	forward (Eigen::MatrixXd &out, const Eigen::MatrixXd &x)
	Forward pass of the dense layer.

void	backward (Eigen::MatrixXd &out, const Eigen::MatrixXd &dx)
	Backward pass of the dense layer.

const Eigen::MatrixXd &	weights () const
	Get weights.

const Eigen::MatrixXd &	biases () const
	Get biases.

const Eigen::MatrixXd &	dweights () const
	Get weights gradients.

const Eigen::MatrixXd &	dbiases () const
	Get biases gradients.

void	weights (Eigen::MatrixXd &weights)
	Set's the weights of the dense layer.

void	biases (Eigen::MatrixXd &biases)
	Set's the biases of the dense layer.

void	weights_optimizer (Eigen::MatrixXd woptimizer)
	Set's the weights optimizer matrix of the dense layer.

void	biases_optimizer (Eigen::MatrixXd boptimizer)
	Set's the biases optimizer matrix of the dense layer.

const Eigen::MatrixXd &	weights_optimizer () const
	Get weights optimizer matrix.

const Eigen::MatrixXd &	biases_optimizer () const
	Get biases optimizer matrix.

void	weights_optimizer_additional (Eigen::MatrixXd woptimizer)
	Set's the additional weights optimizer matrix of the dense layer.

void	biases_optimizer_additional (Eigen::MatrixXd boptimizer)
	Set's the additional biases optimizer matrix of the dense layer.

const Eigen::MatrixXd &	weights_optimizer_additional () const
	Get additional weights optimizer matrix.

const Eigen::MatrixXd &	biases_optimizer_additional () const
	Get additional biases optimizer matrix.

const double &	l1_weights_regularizer () const
	Get L1 weights regularizer.

const double &	l2_weights_regularizer () const
	Get L2 weights regularizer.

const double &	l1_biases_regularizer () const
	Get L1 biases regularizer.

const double &	l2_biases_regularizer () const
	Get L2 biases regularizer.

int	parameters () const
	Calculates the number of trainable of the dense layer.

void	shape (int &n_input, int &n_output) const
	Gives the shape of the dense layer.

Public Member Functions inherited from NNFS::Layer
	Layer (LayerType type)
	Construct a new Layer object.

virtual	~Layer ()=default
	Basic destructor.

virtual void	forward (Eigen::MatrixXd &out, const Eigen::MatrixXd &x)=0
	Forward pass of the layer.

virtual void	backward (Eigen::MatrixXd &out, const Eigen::MatrixXd &dx)=0
	Backward pass of the layer.

Additional Inherited Members
Public Attributes inherited from NNFS::Layer
LayerType	type

Detailed Description

Dense layer.

This class implements the dense layer. It is the most basic layer in a neural network.

Constructor & Destructor Documentation

◆ Dense()

NNFS::Dense::Dense	(	int	n_input,
		int	n_output,
		double	l1_weights_regularizer = `.0`,
		double	l1_biases_regularizer = `.0`,
		double	l2_weights_regularizer = `.0`,
		double	l2_biases_regularizer = `.0`
	)

inline

Construct a new Dense object.

This constructor initializes the weights and biases of the layer. It also sets all regularization matrices to zero.

Parameters

n_input	Number of input neurons
n_output	Number of output neurons
l1_weights_regularizer	L1 regularization for weights (default: 0.0)
l1_biases_regularizer	L1 regularization for biases (default: 0.0)
l2_weights_regularizer	L2 regularization for weights (default: 0.0)
l2_biases_regularizer	L2 regularization for biases (default: 0.0)

Member Function Documentation

◆ backward()

void NNFS::Dense::backward	(	Eigen::MatrixXd &	out,
		const Eigen::MatrixXd &	dx
	)

inlinevirtual

Backward pass of the dense layer.

Parameters

[out]	out	Input gradient
[in]	dx	Output gradient

Implements NNFS::Layer.

◆ biases() [1/2]

const Eigen::MatrixXd & NNFS::Dense::biases ( ) const

inline

Get biases.

Returns: Eigen::MatrixXd& Biases

◆ biases() [2/2]

void NNFS::Dense::biases ( Eigen::MatrixXd & biases )

inline

Set's the biases of the dense layer.

This function sets the biases of the dense layer. The shape of the new biases matrix must match the shape of the initial biases matrix.

Parameters

[in] biases New biases matrix

Exceptions

std::invalid_argument if the shape of the new biases matrix does not match the shape of the initial biases matrix.

◆ biases_optimizer() [1/2]

const Eigen::MatrixXd & NNFS::Dense::biases_optimizer ( ) const

inline

Get biases optimizer matrix.

Returns: Eigen::MatrixXd& Biases optimizer matrix

◆ biases_optimizer() [2/2]

void NNFS::Dense::biases_optimizer ( Eigen::MatrixXd boptimizer )

inline

Set's the biases optimizer matrix of the dense layer.

Parameters

boptimizer New biases optimizer matrix

◆ biases_optimizer_additional() [1/2]

const Eigen::MatrixXd & NNFS::Dense::biases_optimizer_additional ( ) const

inline

Get additional biases optimizer matrix.

Returns: Eigen::MatrixXd& Additional biases optimizer matrix

◆ biases_optimizer_additional() [2/2]

void NNFS::Dense::biases_optimizer_additional ( Eigen::MatrixXd boptimizer )

inline

Set's the additional biases optimizer matrix of the dense layer.

Parameters

boptimizer New additional biases optimizer matrix

◆ dbiases()

const Eigen::MatrixXd & NNFS::Dense::dbiases ( ) const

inline

Get biases gradients.

Returns: Eigen::MatrixXd& Biases gradients

◆ dweights()

const Eigen::MatrixXd & NNFS::Dense::dweights ( ) const

inline

Get weights gradients.

Returns: Eigen::MatrixXd& Weights gradients

◆ forward()

void NNFS::Dense::forward	(	Eigen::MatrixXd &	out,
		const Eigen::MatrixXd &	x
	)

inlinevirtual

Forward pass of the dense layer.

Parameters

[out]	out	Output of the layer
[in]	x	Input of the layer

Implements NNFS::Layer.

◆ l1_biases_regularizer()

const double & NNFS::Dense::l1_biases_regularizer ( ) const

inline

Get L1 biases regularizer.

Returns: double L1 biases regularizer

◆ l1_weights_regularizer()

const double & NNFS::Dense::l1_weights_regularizer ( ) const

inline

Get L1 weights regularizer.

Returns: double L1 weights regularizer

◆ l2_biases_regularizer()

const double & NNFS::Dense::l2_biases_regularizer ( ) const

inline

Get L2 biases regularizer.

Returns: double L2 biases regularizer

◆ l2_weights_regularizer()

const double & NNFS::Dense::l2_weights_regularizer ( ) const

inline

Get L2 weights regularizer.

Returns: double L2 weights regularizer

◆ parameters()

int NNFS::Dense::parameters ( ) const

inline

Calculates the number of trainable of the dense layer.

Returns: int Number of parameters

◆ shape()

void NNFS::Dense::shape	(	int &	n_input,
		int &	n_output
	)		const

inline

Gives the shape of the dense layer.

Parameters

[out]	n_input	Number of input neurons
[out]	n_output	Number of output neurons

◆ weights() [1/2]

const Eigen::MatrixXd & NNFS::Dense::weights ( ) const

inline

Get weights.

Returns: Eigen::MatrixXd& Weights

◆ weights() [2/2]

void NNFS::Dense::weights ( Eigen::MatrixXd & weights )

inline

Set's the weights of the dense layer.

This function sets the weights of the dense layer. The shape of the new weights matrix must match the shape of the initial weights matrix.

Parameters

[in] weights New weights matrix

Exceptions

std::invalid_argument if the shape of the new weights matrix does not match the shape of the initial weights matrix.

◆ weights_optimizer() [1/2]

const Eigen::MatrixXd & NNFS::Dense::weights_optimizer ( ) const

inline

Get weights optimizer matrix.

Returns: Eigen::MatrixXd& Weights optimizer matrix

◆ weights_optimizer() [2/2]

void NNFS::Dense::weights_optimizer ( Eigen::MatrixXd woptimizer )

inline

Set's the weights optimizer matrix of the dense layer.

Parameters

woptimizer New weights optimizer matrix

◆ weights_optimizer_additional() [1/2]

const Eigen::MatrixXd & NNFS::Dense::weights_optimizer_additional ( ) const

inline

Get additional weights optimizer matrix.

Returns: Eigen::MatrixXd& Additional weights optimizer matrix

◆ weights_optimizer_additional() [2/2]

void NNFS::Dense::weights_optimizer_additional ( Eigen::MatrixXd woptimizer )

inline

Set's the additional weights optimizer matrix of the dense layer.

Parameters

woptimizer New additional weights optimizer matrix

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

include/NNFS/Layer/Dense.hpp

Public Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ Dense()

Member Function Documentation

◆ backward()

◆ biases() [1/2]

◆ biases() [2/2]

◆ biases_optimizer() [1/2]

◆ biases_optimizer() [2/2]

◆ biases_optimizer_additional() [1/2]

◆ biases_optimizer_additional() [2/2]

◆ dbiases()

◆ dweights()

◆ forward()

◆ l1_biases_regularizer()

◆ l1_weights_regularizer()

◆ l2_biases_regularizer()

◆ l2_weights_regularizer()

◆ parameters()

◆ shape()

◆ weights() [1/2]

◆ weights() [2/2]

◆ weights_optimizer() [1/2]

◆ weights_optimizer() [2/2]

◆ weights_optimizer_additional() [1/2]

◆ weights_optimizer_additional() [2/2]