PLogPVariable.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

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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: PLogPVariable.cc,v 1.6 2004/04/27 16:02:26 morinf Exp $
   * This file is part of the PLearn library.
   ******************************************************* */

#include "LogVariable.h"
#include "PLogPVariable.h"
#include "Var_operators.h"

namespace PLearn {
using namespace std;


PLEARN_IMPLEMENT_OBJECT(PLogPVariable,
                        "Returns the elementwise x*log(x) in a (hopefully!) numerically stable way",
                        "NO HELP");

PLogPVariable::PLogPVariable(Variable* input)
  : inherited(input, input->length(), input->width())
{}


void PLogPVariable::recomputeSize(int& l, int& w) const
{
    if (input) {
        l = input->length();
        w = input->width();
    } else
        l = w = 0;
}

void PLogPVariable::fprop()
{
  for(int i=0; i<nelems(); i++)
    {
      real p = input->valuedata[i];
      if(p<1e-10)
        p = 1e-10;
      valuedata[i] = p*safeflog(p);
    }
}


void PLogPVariable::bprop()
{
  for(int i=0; i<nelems(); i++)
    {
      real p = input->valuedata[i];
      if(p<1e-10)
        p = 1e-10;
      input->gradientdata[i] += gradientdata[i]*(1.0+safeflog(p));
    }
}


void PLogPVariable::symbolicBprop()
{
  input->accg(g * (1.+log(input)));
}



} // end of namespace PLearn

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