PLearn 0.1
PlusScalarVariable.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: PlusScalarVariable.cc 3994 2005-08-25 13:35:03Z chapados $
00040  * This file is part of the PLearn library.
00041  ******************************************************* */
00042 
00043 #include "PlusScalarVariable.h"
00044 #include "SumVariable.h"
00045 //#include "Var_utils.h"
00046 
00047 namespace PLearn {
00048 using namespace std;
00049 
00050 
00053 PLEARN_IMPLEMENT_OBJECT(PlusScalarVariable,
00054                         "Adds a scalar var to a matrix var",
00055                         "NO HELP");
00056 
00057 PlusScalarVariable::PlusScalarVariable(Variable* input1, Variable* input2)
00058     : inherited(input1, input2, input1->length(), input1->width())
00059 {
00060     build_();
00061 }
00062 
00063 void
00064 PlusScalarVariable::build()
00065 {
00066     inherited::build();
00067     build_();
00068 }
00069 
00070 void
00071 PlusScalarVariable::build_()
00072 {
00073     if(input2 && !input2->isScalar())
00074         PLERROR("IN PlusScalarVariable: input2 is not a scalar");
00075 }
00076 
00077 void PlusScalarVariable::recomputeSize(int& l, int& w) const
00078 {
00079     if (input1) {
00080         l = input1->length();
00081         w = input1->width();
00082     } else
00083         l = w = 0;
00084 }
00085 
00086 
00087 void PlusScalarVariable::fprop()
00088 {
00089     real scal = input2->valuedata[0];
00090     for(int k=0; k<nelems(); k++)
00091         valuedata[k] = input1->valuedata[k] + scal;
00092 }
00093 
00094 
00095 void PlusScalarVariable::bprop()
00096 {
00097     for(int k=0; k<nelems(); k++)
00098     {
00099         input1->gradientdata[k] += gradientdata[k];
00100         input2->gradientdata[0] += gradientdata[k];
00101     }
00102 }
00103 
00104 
00105 void PlusScalarVariable::bbprop()
00106 {
00107     if (input1->diaghessian.length()==0)
00108         input1->resizeDiagHessian();
00109     if (input2->diaghessian.length()==0)
00110         input2->resizeDiagHessian();
00111     for(int k=0; k<nelems(); k++)
00112     {
00113         input1->diaghessiandata[k] += diaghessiandata[k];
00114         input2->diaghessiandata[0] += diaghessiandata[k];
00115     }
00116 }
00117 
00118 
00119 void PlusScalarVariable::symbolicBprop()
00120 {
00121     input1->accg(g);
00122     input2->accg(sum(g));
00123 }
00124 
00125 
00126 
00127 // R(x1+x2) = R(x1) + R(x2)
00128 void PlusScalarVariable::rfprop()
00129 {
00130     if (rValue.length()==0) resizeRValue();
00131     real rscal = input2->rvaluedata[0];
00132     for(int k=0; k<nelems(); k++)
00133         rvaluedata[k] = input1->rvaluedata[k] + rscal;
00134 }
00135 
00136 
00137 
00138 } // end of namespace PLearn
00139 
00140 
00141 /*
00142   Local Variables:
00143   mode:c++
00144   c-basic-offset:4
00145   c-file-style:"stroustrup"
00146   c-file-offsets:((innamespace . 0)(inline-open . 0))
00147   indent-tabs-mode:nil
00148   fill-column:79
00149   End:
00150 */
00151 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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