PLearn 0.1
DotProductVariable.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: DotProductVariable.cc 7068 2007-05-11 22:15:15Z simonl $
00040  * This file is part of the PLearn library.
00041  ******************************************************* */
00042 
00043 #include "DotProductVariable.h"
00044 #include "Var_operators.h"
00045 //#include "Var_utils.h"
00046 
00047 namespace PLearn {
00048 using namespace std;
00049 
00050 
00053 // Dot product between 2 matrices (or vectors) with same number of elements
00054 
00055 PLEARN_IMPLEMENT_OBJECT(DotProductVariable,
00056                         "Dot product between 2 matrices (or vectors) with same number of elements",
00057                         "NO HELP");
00058 
00059 DotProductVariable::DotProductVariable(Variable* input1, Variable* input2)
00060     : inherited(input1, input2, 1, 1)
00061 {
00062     build_();
00063 }
00064 
00065 void
00066 DotProductVariable::build()
00067 {
00068     inherited::build();
00069     build_();
00070 }
00071 
00072 void
00073 DotProductVariable::build_()
00074 {
00075     if(input1 && input2 && (input1->nelems() != input2->nelems()))
00076         PLERROR("IN DotProductVariable input1 and input2 must have the "
00077                 "same number of elements: %dx%d != %dx%d", 
00078                 input1->length(), input1->width(), input2->length(), input2->width());
00079 }
00080 
00081 void DotProductVariable::recomputeSize(int& l, int& w) const
00082 { l=1; w=1; }
00083 
00084 
00085 
00086 
00087 
00088 
00089 
00090 
00091 void DotProductVariable::fprop()
00092 {
00093     real sum = 0.0;
00094     for (int k=0; k<input1->nelems(); k++)
00095         sum += input1->valuedata[k] * input2->valuedata[k];
00096     valuedata[0] = sum;
00097 }
00098 
00099 
00100 void DotProductVariable::bprop()
00101 {
00102     real grad = gradientdata[0];
00103     for (int k=0; k<input1->nelems(); k++)
00104     {
00105         input1->gradientdata[k] += input2->valuedata[k] * grad;
00106         input2->gradientdata[k] += input1->valuedata[k] * grad;
00107     }
00108 }
00109 
00110 
00111 void DotProductVariable::bbprop()
00112 {
00113     if (input1->diaghessian.length()==0)
00114         input1->resizeDiagHessian();
00115     if (input2->diaghessian.length()==0)
00116         input2->resizeDiagHessian();
00117     real h = diaghessiandata[0];
00118     for (int k=0; k<input1->nelems(); k++)
00119     {
00120         real in2v=input2->valuedata[k];
00121         input1->diaghessiandata[k] += in2v * in2v * h;
00122         real in1v=input1->valuedata[k];
00123         input2->diaghessiandata[k] += in1v * in1v * h;
00124     }
00125 }
00126 
00127 
00128 void DotProductVariable::symbolicBprop()
00129 {
00130     input1->accg(input2*g);
00131     input2->accg(input1*g);
00132 }
00133 
00134 
00135 void DotProductVariable::rfprop()
00136 {
00137     if (rValue.length()==0) resizeRValue(); 
00138     real sum = 0.0;
00139     for (int k=0; k<input1->nelems(); k++)
00140         sum += input1->rvaluedata[k] * input2->valuedata[k] + input1->valuedata[k] * input2->rvaluedata[k];
00141     rvaluedata[0] = sum;
00142 }
00143 
00144 
00145 
00146 } // end of namespace PLearn
00147 
00148 
00149 /*
00150   Local Variables:
00151   mode:c++
00152   c-basic-offset:4
00153   c-file-style:"stroustrup"
00154   c-file-offsets:((innamespace . 0)(inline-open . 0))
00155   indent-tabs-mode:nil
00156   fill-column:79
00157   End:
00158 */
00159 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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