SoftmaxVariable.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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/* *******************************************************      
   * $Id: SoftmaxVariable.cc,v 1.5 2004/04/27 16:02:26 morinf Exp $
   * This file is part of the PLearn library.
   ******************************************************* */

#include "SoftmaxVariable.h"

namespace PLearn {
using namespace std;


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

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

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

void SoftmaxVariable::fprop()
{
  softmax(input->value,value);
}


void SoftmaxVariable::bprop()
{
  for(int i=0; i<input->nelems(); i++)
  {
    real vali = valuedata[i];
    for(int k=0; k<nelems(); k++)
    {
      if(k!=i)
        input->gradientdata[i] -= gradientdata[k]*vali*valuedata[k];
      else
        input->gradientdata[i] += gradientdata[i]*vali*(1.-vali);        
    }
  }
}


void SoftmaxVariable::bbprop()
{
  PLERROR("SofmaxVariable::bbprop() not implemented");
}


void SoftmaxVariable::symbolicBprop()
{
  PLERROR("SofmaxVariable::symbolicBprop() not implemented");
}


// R{ s_i = exp(x_i) / sum_j exp(x_j) }   = (s_i(1-s_i) - sum_{k!=i} s_i s_k) R(s_i) = s_i ((1-s_i) - sum_{k!=i} s_k) R(s_i)
void SoftmaxVariable::rfprop()
{
  if (rValue.length()==0) resizeRValue();
  for(int i=0; i<input->nelems(); i++)
  {
    real vali = valuedata[i];
    rvaluedata[i] = vali * (1 - vali) * input->rvaluedata[i];
  }
}



} // end of namespace PLearn

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