LogSoftmaxVariable.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: LogSoftmaxVariable.cc,v 1.5 2004/04/27 15:58:16 morinf Exp $
   * This file is part of the PLearn library.
   ******************************************************* */

#include "LogSoftmaxVariable.h"

namespace PLearn {
using namespace std;


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

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

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

void
LogSoftmaxVariable::fprop()
{
    log_softmax(input->value, value);
}


void
LogSoftmaxVariable::bprop()
{
    for (int i = 0; i < input->nelems(); ++i) {
        real sum = 0.;
        for (int k = 0; k < nelems(); ++k)
            sum += gradientdata[k];
        input->gradientdata[i] += gradientdata[i] - sum * safeexp(valuedata[i]);
    }
}


void
LogSoftmaxVariable::bbprop()
{
    PLERROR("LogSofmaxVariable::bbprop() not implemented");
}


void
LogSoftmaxVariable::symbolicBprop()
{
    PLERROR("LogSofmaxVariable::symbolicBprop() not implemented");
}



} // end of namespace PLearn

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