Public Member Functions
	fc_layer_sm (const std::vector< std::vector< double >> &weights_, const std::vector< double > &biases_)

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

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

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

int	get_num_nodes ()

int	get_input_size ()

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

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

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 ()

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

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

Member Function Documentation

◆ compute_partial_derivatives_wrt_inputs()

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

overridevirtual

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_sm::compute_partial_derivatives_wrt_weights_biases ( Eigen::VectorXd & input )

overridevirtual

Computes the Jacobian matrix with respect to weights and biases.

Implements layer.

◆ predict()

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

overridevirtual

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

Reimplemented from layer.

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

fc_layer_sm.h
fc_layer_sm.cpp

Public Member Functions

Additional Inherited Members

Member Function Documentation

◆ compute_partial_derivatives_wrt_inputs()

◆ compute_partial_derivatives_wrt_weights_biases()

◆ predict()