PLearn 0.1
DivVariable.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: DivVariable.cc 8956 2008-05-08 19:19:03Z tihocan $
00040  * This file is part of the PLearn library.
00041  ******************************************************* */
00042 
00043 #include "DivVariable.h"
00044 #include "InvertElementsVariable.h"
00045 #include "Var_operators.h"
00046 
00047 namespace PLearn {
00048 using namespace std;
00049 
00050 
00053 PLEARN_IMPLEMENT_OBJECT(
00054         DivVariable,
00055         "Divide 2 matrices of same size elementwise",
00056         ""
00057 );
00058 
00060 // DivVariable //
00062 DivVariable::DivVariable(Variable* input1, Variable* input2, bool call_build_):
00063     inherited(input1, input2, input1->length(), input1->width(), call_build_)
00064 {
00065     if (call_build_)
00066         build_();
00067 }
00068 
00070 // recomputeSize //
00072 void DivVariable::recomputeSize(int& l, int& w) const
00073 {
00074     if (input1) {
00075         l = input1->length();
00076         w = input1->width();
00077     } else
00078         l = w = 0;
00079 }
00080 
00082 // build //
00084 void DivVariable::build()
00085 {
00086     inherited::build();
00087     build_();
00088 }
00089 
00091 // build_ //
00093 void DivVariable::build_()
00094 {
00095     if (input1 && input2)
00096         if(input1->length() != input2->length() || input1->width() != input2->width())
00097             PLERROR("In DivVariable: input1 and input2 must have exactly the same shape");
00098 }
00099 
00100 void DivVariable::fprop()
00101 {
00102     for(int k=0; k<nelems(); k++)
00103         valuedata[k] = input1->valuedata[k]/input2->valuedata[k];
00104 }
00105 
00106 
00107 void DivVariable::bprop()
00108 {
00109     for(int k=0; k<nelems(); k++)
00110     {
00111         real iv2k = 1.0/input2->valuedata[k];
00112         input1->gradientdata[k] += gradientdata[k] * iv2k;
00113         input2->gradientdata[k] -= gradientdata[k] * 
00114             input1->valuedata[k] * iv2k * iv2k;
00115     }
00116 }
00117 
00118 
00119 void DivVariable::symbolicBprop()
00120 {
00121     Var iv2 = invertElements(input2);
00122     input1->accg(g * iv2);
00123     input2->accg(-g * input1 * square(iv2));
00124 }
00125 
00126 
00127 void DivVariable::rfprop()
00128 {
00129     if (rValue.length()==0) resizeRValue();
00130   
00131     for(int k=0; k<nelems(); k++)
00132     {
00133         real iv2k = 1.0/input2->valuedata[k];
00134         rvaluedata[k] = input1->rvaluedata[k] * iv2k - input2->rvaluedata[k] * input1->valuedata[k] * iv2k * iv2k;
00135     }
00136 }
00137 
00138 
00139 
00140 } // end of namespace PLearn
00141 
00142 
00143 /*
00144   Local Variables:
00145   mode:c++
00146   c-basic-offset:4
00147   c-file-style:"stroustrup"
00148   c-file-offsets:((innamespace . 0)(inline-open . 0))
00149   indent-tabs-mode:nil
00150   fill-column:79
00151   End:
00152 */
00153 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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