ClassificationLossVariable.h

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// -*- C++ -*-

// PLearn (A C++ Machine Learning Library)
// Copyright (C) 1998 Pascal Vincent
// Copyright (C) 1999-2002 Pascal Vincent, Yoshua Bengio, Rejean Ducharme and University of Montreal
// Copyright (C) 2001-2002 Nicolas Chapados, Ichiro Takeuchi, Jean-Sebastien Senecal
// Copyright (C) 2002 Xiangdong Wang, Christian Dorion

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// modification, are permitted provided that the following conditions are met:
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//  1. Redistributions of source code must retain the above copyright
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/* *******************************************************      
   * $Id: ClassificationLossVariable.h,v 1.5 2004/04/27 15:58:16 morinf Exp $
   * This file is part of the PLearn library.
   ******************************************************* */

#ifndef ClassificationLossVariable_INC
#define ClassificationLossVariable_INC

#include "BinaryVariable.h"
// For inline function that can return either a ClassificationLossVariable or a MiniBatchClassificationLossVariable
#include "MiniBatchClassificationLossVariable.h"

namespace PLearn {
using namespace std;


class ClassificationLossVariable: public BinaryVariable
{
  typedef BinaryVariable inherited;

public:
  ClassificationLossVariable() {}
  ClassificationLossVariable(Variable* netout, Variable* classnum);

  PLEARN_DECLARE_OBJECT(ClassificationLossVariable);

  virtual void build();

  virtual void recomputeSize(int& l, int& w) const;
  virtual void fprop();
  virtual void bprop() {}

protected:
  void build_();
};

DECLARE_OBJECT_PTR(ClassificationLossVariable);

inline Var classification_loss(Var network_output, Var classnum)
{ 
  if(classnum->isScalar())
    return new ClassificationLossVariable(network_output, classnum); 
  else return new MiniBatchClassificationLossVariable(network_output, classnum); 
}


} // end of namespace PLearn

#endif 

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