CrossEntropyVariable.cc

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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

// 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.
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//     documentation and/or other materials provided with the distribution.
// 
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//     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: CrossEntropyVariable.cc,v 1.10 2004/04/27 15:58:16 morinf Exp $
   * This file is part of the PLearn library.
   ******************************************************* */

#include "CrossEntropyVariable.h"

namespace PLearn {
using namespace std;



PLEARN_IMPLEMENT_OBJECT(CrossEntropyVariable,
                        "cost = - sum_i {target_i * log(output_i) + (1-target_i) * log(1-output_i)}",
                        "NO HELP");

CrossEntropyVariable::CrossEntropyVariable(Variable* netout, Variable* target)
  : inherited(netout,target,1,1)
{
    build_();
}

void
CrossEntropyVariable::build()
{
    inherited::build();
    build_();
}

void
CrossEntropyVariable::build_()
{
    // input1 and input2 are (respectively) netout and target from constructor
    if (input1 && input2 && (input1->size() != input2->size()))
        PLERROR("In CrossEntropyVariable: netout and target must have the same size");
}


void CrossEntropyVariable::recomputeSize(int& l, int& w) const
{ l=1, w=1; }


void CrossEntropyVariable::fprop()
{
  real cost = 0.0;
  for (int i=0; i<input1->size(); i++)
  {
    real output = input1->valuedata[i];
    real target = input2->valuedata[i];
    if ((output == 0.0 && target != 0) || (output == 1.0 && target != 1))
      PLERROR("CrossEntropyVariable::fprop: model output is either exactly "
              "0.0 or 1.0; cannot compute cost function");
    if (output != 0 && output != 1) {
      cost += target*log(output) + (1.0-target)*log(1.0-output);
    }
  }
  valuedata[0] = -cost;
}


void CrossEntropyVariable::bprop()
{
  real gr = *gradientdata;
  for (int i=0; i<input1->size(); i++)
  {
    real output = input1->valuedata[i];
    real target = input2->valuedata[i];
#ifdef BOUNDCHECK
    if (output == target)
      PLERROR("CrossEntropyVariable::bprop: model output is either exactly "
              "0.0 or 1.0; cannot compute bprop");
#endif
    input1->gradientdata[i] += gr*(-target/output + (1.0-target)/(1.0-output));
  }
}


} // end of namespace PLearn

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