#include <combine-nnet-a.h>

Collaboration diagram for NnetCombineAconfig:

Public Member Functions
	NnetCombineAconfig ()

void	Register (OptionsItf *opts)

Public Attributes
int32	num_bfgs_iters

BaseFloat	initial_step

BaseFloat	valid_impr_thresh

BaseFloat	overshoot

BaseFloat	min_learning_rate_factor

BaseFloat	max_learning_rate_factor

BaseFloat	min_learning_rate

Detailed Description

Definition at line 31 of file combine-nnet-a.h.

Constructor & Destructor Documentation

◆ NnetCombineAconfig()

NnetCombineAconfig ( )

inline

Definition at line 46 of file combine-nnet-a.h.

                       : num_bfgs_iters(15), initial_step(0.1),
                         valid_impr_thresh(0.5), overshoot(1.8),
                         min_learning_rate_factor(0.5),
                         max_learning_rate_factor(2.0),
                         min_learning_rate(0.0001) { }

Member Function Documentation

◆ Register()

void Register ( OptionsItf * opts )

inline

Definition at line 52 of file combine-nnet-a.h.

References kaldi::nnet2::CombineNnetsA(), and OptionsItf::Register().

                                   {
     opts->Register("num-bfgs-iters", &num_bfgs_iters, "Maximum number of function "
                    "evaluations for BFGS to use when optimizing combination weights");
     opts->Register("initial-step", &initial_step, "Parameter in the optimization, "
                    "used to set the initial step length; the default value should be "
                    "suitable.");
     opts->Register("num-bfgs-iters", &num_bfgs_iters, "Maximum number of function "
                    "evaluations for BFGS to use when optimizing combination weights");
     opts->Register("valid-impr-thresh", &valid_impr_thresh, "Threshold of improvement "
                    "in validation-set objective function for one iteratin; below this, "
                    "we start using the \"overshoot\" mechanism to keep learning rates high.");
     opts->Register("overshoot", &overshoot, "Factor by which we overshoot the step "
                    "size obtained by BFGS; only applies when validation set impr is less "
                    "than valid-impr-thresh.");
     opts->Register("max-learning-rate-factor", &max_learning_rate_factor,
                    "Maximum factor by which to increase the learning rate for any layer.");
     opts->Register("min-learning-rate-factor", &min_learning_rate_factor,
                    "Minimum factor by which to increase the learning rate for any layer.");
     opts->Register("min-learning-rate", &min_learning_rate,
                    "Floor on the automatically updated learning rates");
   }  