PLearn 0.1
SoftmaxVariable.cc
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00001 // -*- C++ -*-
00002 
00003 // PLearn (A C++ Machine Learning Library)
00004 // Copyright (C) 1998 Pascal Vincent
00005 // Copyright (C) 1999-2002 Pascal Vincent, Yoshua Bengio, Rejean Ducharme and University of Montreal
00006 // Copyright (C) 2001-2002 Nicolas Chapados, Ichiro Takeuchi, Jean-Sebastien Senecal
00007 // Copyright (C) 2002 Xiangdong Wang, Christian Dorion
00008 
00009 // Redistribution and use in source and binary forms, with or without
00010 // modification, are permitted provided that the following conditions are met:
00011 // 
00012 //  1. Redistributions of source code must retain the above copyright
00013 //     notice, this list of conditions and the following disclaimer.
00014 // 
00015 //  2. Redistributions in binary form must reproduce the above copyright
00016 //     notice, this list of conditions and the following disclaimer in the
00017 //     documentation and/or other materials provided with the distribution.
00018 // 
00019 //  3. The name of the authors may not be used to endorse or promote
00020 //     products derived from this software without specific prior written
00021 //     permission.
00022 // 
00023 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00024 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00025 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00026 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00027 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00028 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00029 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00030 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00031 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00032 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00033 // 
00034 // This file is part of the PLearn library. For more information on the PLearn
00035 // library, go to the PLearn Web site at www.plearn.org
00036 
00037 
00038 /* *******************************************************      
00039  * $Id: SoftmaxVariable.cc 8848 2008-04-21 20:51:04Z tihocan $
00040  * This file is part of the PLearn library.
00041  ******************************************************* */
00042 
00043 #include "SoftmaxVariable.h"
00044 
00045 namespace PLearn {
00046 using namespace std;
00047 
00048 
00051 PLEARN_IMPLEMENT_OBJECT(
00052         SoftmaxVariable,
00053        "Softmax of its input variable.",
00054        ""
00055 );
00056 
00057 SoftmaxVariable::SoftmaxVariable(Variable* input) 
00058     : inherited(input, input->length(), input->width())
00059 {}
00060 
00061 void SoftmaxVariable::recomputeSize(int& l, int& w) const
00062 {
00063     if (input) {
00064         l = input->length();
00065         w = input->width();
00066     } else
00067         l = w = 0;
00068 }
00069 
00070 void SoftmaxVariable::fprop()
00071 {
00072     softmax(input->value,value);
00073 }
00074 
00075 
00076 void SoftmaxVariable::bprop()
00077 {
00078     for(int i=0; i<input->nelems(); i++)
00079     {
00080         real vali = valuedata[i];
00081         for(int k=0; k<nelems(); k++)
00082         {
00083             if(k!=i)
00084                 input->gradientdata[i] -= gradientdata[k]*vali*valuedata[k];
00085             else
00086                 input->gradientdata[i] += gradientdata[i]*vali*(1.-vali);        
00087         }
00088     }
00089 }
00090 
00091 
00092 void SoftmaxVariable::bbprop()
00093 {
00094     PLERROR("SofmaxVariable::bbprop() not implemented");
00095 }
00096 
00097 
00098 void SoftmaxVariable::symbolicBprop()
00099 {
00100     PLERROR("SofmaxVariable::symbolicBprop() not implemented");
00101 }
00102 
00103 
00104 // 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)
00105 void SoftmaxVariable::rfprop()
00106 {
00107     if (rValue.length()==0) resizeRValue();
00108     for(int i=0; i<input->nelems(); i++)
00109     {
00110         real vali = valuedata[i];
00111         rvaluedata[i] = vali * (1 - vali) * input->rvaluedata[i];
00112     }
00113 }
00114 
00115 
00116 
00117 } // end of namespace PLearn
00118 
00119 
00120 /*
00121   Local Variables:
00122   mode:c++
00123   c-basic-offset:4
00124   c-file-style:"stroustrup"
00125   c-file-offsets:((innamespace . 0)(inline-open . 0))
00126   indent-tabs-mode:nil
00127   fill-column:79
00128   End:
00129 */
00130 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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