BinaryClassificationLossVariable.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
// Copyright (C) 2004 Olivier Delalleau

// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
// 
//  1. Redistributions of source code must retain the above copyright
//     notice, this list of conditions and the following disclaimer.
// 
//  2. Redistributions in binary form must reproduce the above copyright
//     notice, this list of conditions and the following disclaimer in the
//     documentation and/or other materials provided with the distribution.
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//  3. The name of the authors may not be used to endorse or promote
//     products derived from this software without specific prior written
//     permission.
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// THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
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/* *******************************************************      
   * $Id: BinaryClassificationLossVariable.h,v 1.3 2004/04/27 15:58:16 morinf Exp $
   * This file is part of the PLearn library.
   ******************************************************* */

#ifndef BinaryClassificationLossVariable_INC
#define BinaryClassificationLossVariable_INC

#include "BinaryVariable.h"

namespace PLearn {
using namespace std;


class BinaryClassificationLossVariable: public BinaryVariable
{
  typedef BinaryVariable inherited;

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

  PLEARN_DECLARE_OBJECT(BinaryClassificationLossVariable);

  virtual void build();

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

protected:
  void build_();
};

DECLARE_OBJECT_PTR(BinaryClassificationLossVariable);

inline Var binary_classification_loss(Var network_output, Var classnum)
{ 
  if (classnum->isScalar()) {
    return new BinaryClassificationLossVariable(network_output, classnum); 
  } else {
    PLERROR("In binary_classification_loss : Can only be used with a scalar output");
    // The line below is just for the compiler to stop complaining.
    return new BinaryClassificationLossVariable(network_output, classnum);
  }
}

} // end of namespace PLearn

#endif 

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