PLearn 0.1
LogSoftSoftMaxVariable.cc
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00001 // -*- C++ -*-
00002 
00003 // LogSoftSoftMaxVariable.cc
00004 //
00005 // Copyright (C) 2007 Simon Lemieux, Pascal Vincent
00006 //
00007 // Redistribution and use in source and binary forms, with or without
00008 // modification, are permitted provided that the following conditions are met:
00009 //
00010 //  1. Redistributions of source code must retain the above copyright
00011 //     notice, this list of conditions and the following disclaimer.
00012 //
00013 //  2. Redistributions in binary form must reproduce the above copyright
00014 //     notice, this list of conditions and the following disclaimer in the
00015 //     documentation and/or other materials provided with the distribution.
00016 //
00017 //  3. The name of the authors may not be used to endorse or promote
00018 //     products derived from this software without specific prior written
00019 //     permission.
00020 //
00021 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00022 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00023 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00024 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00025 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00026 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00027 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00028 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00029 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00030 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00031 //
00032 // This file is part of the PLearn library. For more information on the PLearn
00033 // library, go to the PLearn Web site at www.plearn.org
00034 
00035 // Authors: Simon Lemieux, Pascal Vincent
00036 
00040 #include "LogSoftSoftMaxVariable.h"
00041 
00042 namespace PLearn {
00043 using namespace std;
00044 
00047 PLEARN_IMPLEMENT_OBJECT(
00048     LogSoftSoftMaxVariable,
00049     "Kind of softmax variable",
00050     "Let X:=input1, A:=input2\nThen output(n,k) = X(n,k) - log(sum_j{ exp[ X(n,j) + A(k,j) ] })"
00051     );
00052 
00053 
00054 // constructor from input variables.
00055 LogSoftSoftMaxVariable::LogSoftSoftMaxVariable(Variable* input1, Variable* input2)
00056     : inherited(input1, input2, input1->length(), input1->width())
00057 {
00058     build_();
00059 }
00060 
00061 
00062 void LogSoftSoftMaxVariable::recomputeSize(int& l, int& w) const
00063 {
00064         if (input1) {
00065             l = input1->length(); // the computed length of this Var
00066             w = input1->width(); // the computed width
00067         } else
00068             l = w = 0;
00069 }
00070 
00071 // ### computes value from input1 and input2 values
00072 void LogSoftSoftMaxVariable::fprop()
00073 {
00074     Mat X = input1->matValue,
00075         A = input2->matValue;
00076 
00077     real sum;
00078 
00079     for (int n=0; n<X.length(); n++)    
00080         for (int k=0; k<X.width(); k++)
00081         {
00082             sum=0;
00083             for (int i=0; i<X.width(); i++)
00084                 sum += safeexp(X(n,i) + A(k,i));
00085             matValue(n,k) = X(n,k) - safelog(sum);
00086         }    
00087 }
00088 
00089 // ### computes input1 and input2 gradients from gradient
00090 void LogSoftSoftMaxVariable::bprop()
00091 {
00092     Mat X = input1->matValue,
00093         A = input2->matValue,
00094         grad_X = input1->matGradient,
00095         grad_A = input2->matGradient;
00096 
00097     real temp;
00098 
00099     //chacun des exemples de X
00100     for (int n=0; n<X.length(); n++)
00101         //chaque coordonné dun exemple //correspond au gradient
00102         for (int k=0; k<X.width(); k++)
00103             //même exemple, coordonnée aussi // correspond à un exemple
00104             for (int j=0; j<X.width(); j++)
00105             {
00106                 temp = matGradient(n,j)*safeexp(matValue(n,j) + X(n,k) + A(j,k) - X(n,j));
00107 
00108                 if(k==j)
00109                     grad_X(n,k) += matGradient(n,j)*(1.-safeexp(matValue(n,k)));
00110                 else
00111                     grad_X(n,k) -= temp;                    
00112                                                                                             
00113                 grad_A(j,k) -= temp;
00114             }
00115 }
00116 
00117 // ### You can implement these methods:
00118 // void LogSoftSoftMaxVariable::bbprop() {}
00119 // void LogSoftSoftMaxVariable::symbolicBprop() {}
00120 // void LogSoftSoftMaxVariable::rfprop() {}
00121 
00122 
00123 // ### Nothing to add here, simply calls build_
00124 void LogSoftSoftMaxVariable::build()
00125 {
00126     inherited::build();
00127     build_();
00128 }
00129 
00130 void LogSoftSoftMaxVariable::makeDeepCopyFromShallowCopy(CopiesMap& copies)
00131 {
00132     inherited::makeDeepCopyFromShallowCopy(copies);
00133 
00134     // ### Call deepCopyField on all "pointer-like" fields
00135     // ### that you wish to be deepCopied rather than
00136     // ### shallow-copied.
00137     // ### ex:
00138     // deepCopyField(trainvec, copies);
00139 
00140     // ### If you want to deepCopy a Var field:
00141     // varDeepCopyField(somevariable, copies);
00142 
00143     // ### Remove this line when you have fully implemented this method.
00144     PLERROR("LogSoftSoftMaxVariable::makeDeepCopyFromShallowCopy not fully (correctly) implemented yet!");
00145 }
00146 
00147 void LogSoftSoftMaxVariable::declareOptions(OptionList& ol)
00148 {
00149     // ### Declare all of this object's options here.
00150     // ### For the "flags" of each option, you should typically specify
00151     // ### one of OptionBase::buildoption, OptionBase::learntoption or
00152     // ### OptionBase::tuningoption. If you don't provide one of these three,
00153     // ### this option will be ignored when loading values from a script.
00154     // ### You can also combine flags, for example with OptionBase::nosave:
00155     // ### (OptionBase::buildoption | OptionBase::nosave)
00156 
00157     // ### ex:
00158     // declareOption(ol, "myoption", &LogSoftSoftMaxVariable::myoption,
00159     //               OptionBase::buildoption,
00160     //               "Help text describing this option");
00161     // ...
00162 
00163     // Now call the parent class' declareOptions
00164     inherited::declareOptions(ol);
00165 }
00166 
00167 void LogSoftSoftMaxVariable::build_()
00168 {
00169     // ### This method should do the real building of the object,
00170     // ### according to set 'options', in *any* situation.
00171     // ### Typical situations include:
00172     // ###  - Initial building of an object from a few user-specified options
00173     // ###  - Building of a "reloaded" object: i.e. from the complete set of
00174     // ###    all serialised options.
00175     // ###  - Updating or "re-building" of an object after a few "tuning"
00176     // ###    options have been modified.
00177     // ### You should assume that the parent class' build_() has already been
00178     // ### called.
00179 
00180     if (input2.length() != input1.width() || input2.width() != input1.width())
00181         PLERROR("Length and width of input2 must be equal to width of input1 in LogSoftSoftMaxVariable");
00182 }
00183 
00184 
00185 } // end of namespace PLearn
00186 
00187 
00188 /*
00189   Local Variables:
00190   mode:c++
00191   c-basic-offset:4
00192   c-file-style:"stroustrup"
00193   c-file-offsets:((innamespace . 0)(inline-open . 0))
00194   indent-tabs-mode:nil
00195   fill-column:79
00196   End:
00197 */
00198 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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