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NnetFixConfig Struct Reference

#include <nnet-fix.h>

Collaboration diagram for NnetFixConfig:

Public Member Functions

 NnetFixConfig ()
 
void Register (OptionsItf *opts)
 

Public Attributes

BaseFloat min_average_deriv
 
BaseFloat max_average_deriv
 
BaseFloat parameter_factor
 
BaseFloat relu_bias_change
 

Detailed Description

Definition at line 42 of file nnet-fix.h.

Constructor & Destructor Documentation

NnetFixConfig ( )
inline

Definition at line 52 of file nnet-fix.h.

53  parameter_factor(2.0), relu_bias_change(1.0) { }

Member Function Documentation

void Register ( OptionsItf opts)
inline

Definition at line 54 of file nnet-fix.h.

References OptionsItf::Register().

Referenced by main().

54  {
55  opts->Register("min-average-deriv", &min_average_deriv, "Miniumum derivative, "
56  "averaged over the training data, that we allow for a nonlinearity,"
57  "expressed relative to the maximum derivative of the nonlinearity,"
58  "i.e. 1.0 for tanh or 0.25 for sigmoid, 1.0 for rectified linear.");
59  opts->Register("max-average-deriv", &max_average_deriv, "Maximum derivative, "
60  "averaged over the training data, that we allow for the nonlinearity "
61  "associated with one neuron.");
62  opts->Register("parameter-factor", &parameter_factor, "Maximum factor by which we change "
63  "the set of parameters associated with a neuron.");
64  opts->Register("relu-bias-change", &relu_bias_change, "For ReLUs, change in bias when "
65  "we identify a component that's too frequently on or off.");
66  }

Member Data Documentation

BaseFloat max_average_deriv

Definition at line 46 of file nnet-fix.h.

Referenced by kaldi::nnet2::FixNnet().

BaseFloat min_average_deriv

Definition at line 43 of file nnet-fix.h.

Referenced by kaldi::nnet2::FixNnet().

BaseFloat parameter_factor

Definition at line 48 of file nnet-fix.h.

Referenced by kaldi::nnet2::FixNnet().

BaseFloat relu_bias_change

Definition at line 50 of file nnet-fix.h.

Referenced by kaldi::nnet2::FixNnet().


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