PLearn 0.1
WeightedSumSquareVariable.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: WeightedSumSquareVariable.cc 3994 2005-08-25 13:35:03Z chapados $
00040  * This file is part of the PLearn library.
00041  ******************************************************* */
00042 
00043 #include "WeightedSumSquareVariable.h"
00044 #include "Var_operators.h"
00045 
00046 namespace PLearn {
00047 using namespace std;
00048 
00051 PLEARN_IMPLEMENT_OBJECT(WeightedSumSquareVariable,
00052                         "ONE LINE DESCR",
00053                         "NO HELP");
00054 
00055 WeightedSumSquareVariable::WeightedSumSquareVariable(Variable* input, Variable* weights)
00056     : inherited(input,weights,1,1)
00057 {
00058     build_();
00059 }
00060 
00061 void
00062 WeightedSumSquareVariable::build()
00063 {
00064     inherited::build();
00065     build_();
00066 }
00067 
00068 void
00069 WeightedSumSquareVariable::build_()
00070 {
00071     if (input1 && input2) {
00072         // input1 and input2 are (respectively) input and weights from constructor
00073         if (input1->nelems() != input2->nelems())
00074             PLERROR("In WeightedSumSquareVariable: input and weights must be the same size;"
00075                     " input->nelems()=%d weights->nelems()=&d.",
00076                     input1->nelems(), input2->nelems());
00077     }
00078 }
00079 
00080 
00081 void WeightedSumSquareVariable::recomputeSize(int& l, int& w) const
00082 { l=1; w=1; }
00083 
00084 
00085 void WeightedSumSquareVariable::fprop()
00086 {
00087     int n=input1->nelems();
00088     *valuedata= 0;
00089     for(int i=0; i<n; i++)
00090         *valuedata+= input1->valuedata[i]*input1->valuedata[i] * input2->valuedata[i];
00091 }
00092 
00093 
00094 void WeightedSumSquareVariable::bprop()
00095 {
00096     int n=input1->nelems();
00097     for(int i=0; i<n; i++)
00098     {
00099         input1->gradientdata[i]+= 2.0 * input1->valuedata[i] * input2->valuedata[i] * *gradientdata;
00100         input2->gradientdata[i]+= input1->valuedata[i] * input1->valuedata[i] * *gradientdata;
00101     }
00102 }
00103 
00104 
00105 void WeightedSumSquareVariable::symbolicBprop()
00106 {
00107     input1->accg(2.0 * (g*input1*input2));
00108     input2->accg(g*input1*input1);
00109 }
00110 
00111 
00112 
00113 } // end of namespace PLearn
00114 
00115 
00116 /*
00117   Local Variables:
00118   mode:c++
00119   c-basic-offset:4
00120   c-file-style:"stroustrup"
00121   c-file-offsets:((innamespace . 0)(inline-open . 0))
00122   indent-tabs-mode:nil
00123   fill-column:79
00124   End:
00125 */
00126 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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