IsMissingVariable.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: IsMissingVariable.cc,v 1.5 2004/04/27 15:59:16 morinf Exp $
   * This file is part of the PLearn library.
   ******************************************************* */

#include "IsMissingVariable.h"

namespace PLearn {
using namespace std;


PLEARN_IMPLEMENT_OBJECT(IsMissingVariable,
                        "ONE LINE DESCR",
                        "NO HELP");

IsMissingVariable::IsMissingVariable(Variable* input1, bool parall)
    : inherited(input1, parall?input1->length():1, parall?input1->width():1), parallel(parall)
{}

void
IsMissingVariable::declareOptions(OptionList &ol)
{
    declareOption(ol, "parallel", &IsMissingVariable::parallel, OptionBase::buildoption, "");
    inherited::declareOptions(ol);
}

void IsMissingVariable::recomputeSize(int& l, int& w) const
{
    if (input) {
        l = input->length();
        w = parallel ? input->width() : 1;
    } else
        l = w = 0;
}

void IsMissingVariable::fprop()
{
  if (parallel)
    for(int i=0; i<nelems(); i++)
      valuedata[i] = finite(input->valuedata[i]);
  else
    {
      bool nomissing=true;
      for(int i=0; i<nelems(); i++)
        nomissing = nomissing && finite(input->valuedata[i]);
      valuedata[0] = !nomissing;
    }
}


// not really differentiable (zero gradient almost everywhere)
void IsMissingVariable::bprop() {}

void IsMissingVariable::symbolicBprop() {}



} // end of namespace PLearn

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