fc_layer_sp Class Reference

Feedforward layer with softplus activation function. More...

#include <fc_layer_sp.h>

Public Member Functions
	fc_layer_sp ()
	fc_layer_sp (const std::vector< std::vector< double >> &weights_, const std::vector< double > &biases_)
	fc_layer_sp (const Eigen::MatrixXd &weights_, const Eigen::VectorXd &biases_)
	fc_layer_sp (const Eigen::MatrixXd &weights_, const std::vector< double > &biases_)
	~fc_layer_sp ()
Eigen::VectorXd	predict (const Eigen::VectorXd &input) override
std::vector< Eigen::VectorXd >	predict_batch (const std::vector< Eigen::VectorXd > &input) override
Eigen::MatrixXd	compute_partial_derivatives_wrt_inputs (Eigen::VectorXd &input)
Eigen::MatrixXd	compute_partial_derivatives_wrt_weights_biases (Eigen::VectorXd &input)
Public Member Functions inherited from layer
	layer ()
	layer (const std::vector< std::vector< double >> &weights_, const std::vector< double > &biases_)
	layer (const std::vector< std::vector< double >> &weights_)
	layer (const Eigen::MatrixXd &weights_)
	layer (const Eigen::MatrixXd &weights_, const std::vector< double > &biases_)
	layer (const Eigen::MatrixXd &weights_, const Eigen::VectorXd &biases_)
	layer (const Eigen::MatrixXd &weights_, const Eigen::VectorXd &biases_, int in_dim, int out_dim)
virtual	~layer ()
const Eigen::VectorXd	get_biases ()
const Eigen::MatrixXd	get_weights ()
const Eigen::MatrixXd	get_weights_biases_as_mat ()
const Eigen::MatrixXd	get_weights_biases_as_vec_col_maj ()
const Eigen::MatrixXd	get_weights_biases_as_vec_row_maj ()
double	get_weight (int i, int j)
double	get_bias (int i)
void	set_biases (const Eigen::VectorXd &biases_)
void	set_biases (const std::vector< double > &biases_)
void	set_weights (const Eigen::MatrixXd &weights_)
void	set_weight (int i, int j, double weight_)
void	set_bias (int i, double bias_)
void	set_weights_biases_compact (Eigen::MatrixXd &source)
void	set_weights_biases (Eigen::MatrixXd &source)
void	set_weights_biases_row_maj (Eigen::MatrixXd &source)
int	get_num_nodes ()
int	get_input_size ()
int	get_weights_rows ()
int	get_weights_cols ()
std::string	get_type ()
void	transpose_weights ()
void	set_exp_max_cut (double exp_max_cut_)
void	set_exp_zero_approx (double exp_zero_approx_)
double	get_exp_max_cut ()
double	get_exp_zero_approx ()

Additional Inherited Members
Protected Attributes inherited from layer
Eigen::VectorXd	biases
Eigen::MatrixXd	weights
int	weights_rows = 0
int	input_dim = 0
int	output_dim = 0
int	weights_cols = 0
std::string	type
double	exp_max_cut = 50.
double	exp_zero_approx = 1.92874984e-22

Detailed Description

Feedforward layer with softplus activation function.

Constructor & Destructor Documentation

fc_layer_sp() [1/4]

fc_layer_sp::fc_layer_sp ( )

inline

Default constructor.

fc_layer_sp() [2/4]

fc_layer_sp::fc_layer_sp	(	const std::vector< std::vector< double >> &	weights_,
		const std::vector< double > &	biases_
	)

Initializes a feedforward layer with softplus activation function given a matrix of weights and a vector of biases.

fc_layer_sp() [3/4]

fc_layer_sp::fc_layer_sp	(	const Eigen::MatrixXd &	weights_,
		const Eigen::VectorXd &	biases_
	)

Initializes a feedforward layer with softplus activation function given a matrix of weights and a vector of biases.

fc_layer_sp() [4/4]

fc_layer_sp::fc_layer_sp	(	const Eigen::MatrixXd &	weights_,
		const std::vector< double > &	biases_
	)

Initializes a feedforward layer with softplus activation function given a matrix of weights and a vector of biases.

~fc_layer_sp()

fc_layer_sp::~fc_layer_sp ( )

inline

Default deconstructor.

Member Function Documentation

compute_partial_derivatives_wrt_inputs()

Eigen::MatrixXd fc_layer_sp::compute_partial_derivatives_wrt_inputs ( Eigen::VectorXd &  input )

virtual

Computes the Jacobian matrix with respect to the input variables. The Jacobian is computer in reduced form.

Implements layer.

compute_partial_derivatives_wrt_weights_biases()

Eigen::MatrixXd fc_layer_sp::compute_partial_derivatives_wrt_weights_biases ( Eigen::VectorXd &  input )

virtual

Computes the Jacobian matrix with respect to weights and biases.

Implements layer.

predict()

Eigen::VectorXd fc_layer_sp::predict ( const Eigen::VectorXd &  input )

overridevirtual

Computes the output of the layer given an Eigen::VectorXd as input.

Reimplemented from layer.

predict_batch()

std::vector< Eigen::VectorXd > fc_layer_sp::predict_batch ( const std::vector< Eigen::VectorXd > &  input )

overridevirtual

Computes the outputs of the layer given a vector<Eigen::VectorXd> as input.

Reimplemented from layer.

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

• fc_layer_sp.h
• fc_layer_sp.cpp