PLearn::OneHotSquaredLoss Class Reference

Computes sum(square_i(netout[i]-(i==classnum ?hotval :coldval)) This is used typically in a classification setting where netout is a Var of network outputs, and classnum is the target class number. More...

#include <OneHotSquaredLoss.h>

Inheritance diagram for PLearn::OneHotSquaredLoss:

[legend]Collaboration diagram for PLearn::OneHotSquaredLoss:

[legend]List of all members.

Public Member Functions
	OneHotSquaredLoss ()
	Default constructor for persistence.
	OneHotSquaredLoss (Variable *netout, Variable *classnum, real coldval=0., real hotval=1.)
	PLEARN_DECLARE_OBJECT (OneHotSquaredLoss)
virtual void	build ()
	Should call simply inherited::build(), then this class's build_().
virtual void	recomputeSize (int &l, int &w) const
	Recomputes the length l and width w that this variable should have, according to its parent variables.
virtual void	fprop ()
	compute output given input
virtual void	bprop ()
virtual void	symbolicBprop ()
	compute a piece of new Var graph that represents the symbolic derivative of this Var
virtual void	rfprop ()
Static Public Member Functions
void	declareOptions (OptionList &ol)
	redefine this in subclasses: call declareOption(...) for each option, and then call inherited::declareOptions(options) ( see the declareOption function further down)
Protected Member Functions
void	build_ ()
Protected Attributes
real	coldval_
real	hotval_
Private Types
typedef BinaryVariable	inherited

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Detailed Description

Computes sum(square_i(netout[i]-(i==classnum ?hotval :coldval)) This is used typically in a classification setting where netout is a Var of network outputs, and classnum is the target class number.

Definition at line 59 of file OneHotSquaredLoss.h.

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Member Typedef Documentation

typedef BinaryVariable PLearn::OneHotSquaredLoss::inherited [private]

Reimplemented from PLearn::BinaryVariable. Definition at line 61 of file OneHotSquaredLoss.h. Referenced by OneHotSquaredLoss().

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Constructor & Destructor Documentation

PLearn::OneHotSquaredLoss::OneHotSquaredLoss (   )  [inline]

Default constructor for persistence. Definition at line 68 of file OneHotSquaredLoss.h.

PLearn::OneHotSquaredLoss::OneHotSquaredLoss (  Variable *  netout, Variable *  classnum, real  coldval = 0., real  hotval = 1. )

Definition at line 58 of file OneHotSquaredLoss.cc. References build_(), and inherited.

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Member Function Documentation

void PLearn::OneHotSquaredLoss::bprop (   )  [virtual]

Implements PLearn::Variable. Definition at line 102 of file OneHotSquaredLoss.cc. References coldval_, hotval_, and PLearn::two().

void PLearn::OneHotSquaredLoss::build (   )  [virtual]

Should call simply inherited::build(), then this class's build_(). This method should be callable again at later times, after modifying some option fields to change the "architecture" of the object. Reimplemented from PLearn::Variable. Definition at line 65 of file OneHotSquaredLoss.cc. References build_().

void PLearn::OneHotSquaredLoss::build_ (   )  [protected]

This method should be redefined in subclasses and do the actual building of the object according to previously set option fields. Constructors can just set option fields, and then call build_. This method is NOT virtual, and will typically be called only from three places: a constructor, the public virtual build() method, and possibly the public virtual read method (which calls its parent's read). build_() can assume that it's parent's build_ has already been called. Reimplemented from PLearn::Variable. Definition at line 72 of file OneHotSquaredLoss.cc. References PLERROR. Referenced by build(), and OneHotSquaredLoss().

void PLearn::OneHotSquaredLoss::declareOptions (  OptionList &  ol  )  [static]

redefine this in subclasses: call declareOption(...) for each option, and then call inherited::declareOptions(options) ( see the declareOption function further down) ex: static void declareOptions(OptionList& ol) { declareOption(ol, "inputsize", &MyObject::inputsize_, OptionBase::buildoption, "the size of the input\n it must be provided"); declareOption(ol, "weights", &MyObject::weights, OptionBase::learntoption, "the learnt model weights"); inherited::declareOptions(ol); } Reimplemented from PLearn::BinaryVariable. Definition at line 80 of file OneHotSquaredLoss.cc. References PLearn::declareOption(), and PLearn::OptionList.

void PLearn::OneHotSquaredLoss::fprop (   )  [virtual]

compute output given input Implements PLearn::Variable. Definition at line 90 of file OneHotSquaredLoss.cc. References coldval_, hotval_, and PLearn::square().

PLearn::OneHotSquaredLoss::PLEARN_DECLARE_OBJECT (  OneHotSquaredLoss   )

void PLearn::OneHotSquaredLoss::recomputeSize (  int &  l, int &  w )  const [virtual]

Recomputes the length l and width w that this variable should have, according to its parent variables. This is used for ex. by sizeprop() The default version stupidly returns the current dimensions, so make sure to overload it in subclasses if this is not appropriate. Reimplemented from PLearn::Variable. Definition at line 87 of file OneHotSquaredLoss.cc.

void PLearn::OneHotSquaredLoss::rfprop (   )  [virtual]

Reimplemented from PLearn::Variable. Definition at line 132 of file OneHotSquaredLoss.cc. References coldval_, hotval_, and PLearn::sum().

void PLearn::OneHotSquaredLoss::symbolicBprop (   )  [virtual]

compute a piece of new Var graph that represents the symbolic derivative of this Var Reimplemented from PLearn::Variable. Definition at line 123 of file OneHotSquaredLoss.cc. References coldval_, hotval_, and PLearn::Var::length().

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Member Data Documentation

real PLearn::OneHotSquaredLoss::coldval_ [protected]

Definition at line 64 of file OneHotSquaredLoss.h. Referenced by bprop(), fprop(), rfprop(), and symbolicBprop().

real PLearn::OneHotSquaredLoss::hotval_ [protected]

Definition at line 64 of file OneHotSquaredLoss.h. Referenced by bprop(), fprop(), rfprop(), and symbolicBprop().

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

• OneHotSquaredLoss.h
• OneHotSquaredLoss.cc

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