PLearn 0.1
MatrixAffineTransformVariable.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: MatrixAffineTransformVariable.cc 3994 2005-08-25 13:35:03Z chapados $
00040  * This file is part of the PLearn library.
00041  ******************************************************* */
00042 
00043 #include "MatrixAffineTransformVariable.h"
00044 #include "SubMatVariable.h"
00045 #include "ProductVariable.h"
00046 #include "MatrixAffineTransformFeedbackVariable.h"
00047 
00048 namespace PLearn {
00049 using namespace std;
00050 
00051 
00052 PLEARN_IMPLEMENT_OBJECT(MatrixAffineTransformVariable,
00053                         "ONE LINE DESCR",
00054                         "NO HELP");
00055 
00056 void MatrixAffineTransformVariable::recomputeSize(int& l, int& w) const
00057 {
00058     if (input1 && input2) {
00059         l = input2->width();
00060         w = input1->width();
00061     } else
00062         l = w = 0;
00063 }
00064 
00065 
00066 void MatrixAffineTransformVariable::fprop()
00067 {
00068     Mat lintransform = input2->matValue.subMatRows(1,input2->length()-1);
00069     for (int i = 0; i < length(); i++)
00070         for (int j = 0; j < width(); j++)
00071             matValue[i][j] = input2->matValue[0][i];
00072     transposeProductAcc(matValue,lintransform, input1->matValue);
00073 }
00074 
00075 
00076 void MatrixAffineTransformVariable::bprop()
00077 {
00078     Mat&  afftr = input2->matValue;
00079     int l = afftr.length();
00080     Mat lintr = afftr.subMatRows(1,l-1);
00081 
00082     Mat& afftr_g = input2->matGradient;
00083     Vec bias_g = afftr_g.firstRow();
00084     Mat lintr_g = afftr_g.subMatRows(1,l-1);
00085 
00086     for (int i = 0; i < length(); i++)
00087         for (int j = 0; j < width(); j++)
00088         {
00089             bias_g[i] += matGradient[i][j];
00090         }
00091     if(!input1->dont_bprop_here)      
00092         productAcc(input1->matGradient, lintr, matGradient);
00093     productTransposeAcc(lintr_g, input1->matValue, matGradient);
00094 }
00095 
00096 
00097 void MatrixAffineTransformVariable::symbolicBprop()
00098 {
00099     Var lintr = new SubMatVariable(input2,0,0,input2->length()-1,input2->width());
00100     //Var bias = new SubMatVariable(input2,length()-1,0,1,width());
00101 
00102     if(!input1->dont_bprop_here)
00103         input1->accg(new ProductVariable(lintr,g));
00104     input2->accg(new MatrixAffineTransformFeedbackVariable(input1,g));
00105 }
00106 
00107 
00108 
00109 } // end of namespace PLearn
00110 
00111 
00112 /*
00113   Local Variables:
00114   mode:c++
00115   c-basic-offset:4
00116   c-file-style:"stroustrup"
00117   c-file-offsets:((innamespace . 0)(inline-open . 0))
00118   indent-tabs-mode:nil
00119   fill-column:79
00120   End:
00121 */
00122 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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