PLearn 0.1
ConvolveVariable.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: ConvolveVariable.cc 3994 2005-08-25 13:35:03Z chapados $
00040  * This file is part of the PLearn library.
00041  ******************************************************* */
00042 
00043 #include "ConvolveVariable.h"
00044 
00045 namespace PLearn {
00046 using namespace std;
00047 
00048 
00051 PLEARN_IMPLEMENT_OBJECT(ConvolveVariable,
00052                         "A convolve var; equals convolve(input, mask)",
00053                         "NO HELP");
00054 
00055 ConvolveVariable::ConvolveVariable(Variable* input, Variable* mask)
00056     : inherited(input, mask, input->length()-mask->length()+1, input->width()-mask->width()+1)
00057 {}
00058 
00059 
00060 void ConvolveVariable::recomputeSize(int& l, int& w) const
00061 {
00062     if (input1 && input2) {
00063         l = input1->length() - input2->length() + 1;
00064         w = input1->width() - input2->width() + 1;
00065     } else
00066         l = w = 0;
00067 }
00068 
00069 
00070 void ConvolveVariable::fprop()
00071 {
00072     convolve(input1->matValue, input2->matValue, matValue);
00073 }
00074 
00075 
00076 void ConvolveVariable::bprop()
00077 {
00078     for(int i=0; i<length(); i++) // size of matGradient
00079         for(int j=0; j<width(); j++)
00080         {
00081             real* input1valueptr = input1->matValue[i]+j;
00082             real* input2valueptr = input2->matValue.data();
00083         
00084             real thisgradient = matGradient(i,j);
00085             real* input1gradientptr = input1->matGradient[i]+j;
00086             real* input2gradientptr = input2->matGradient.data();
00087         
00088             for(int l=0; l<input2->length(); l++,
00089                     input1valueptr += input1->matValue.mod(), input2valueptr += input2->matValue.mod(),
00090                     input1gradientptr += input1->matGradient.mod(), input2gradientptr += input2->matGradient.mod())
00091                 for(int c=0; c<input2->width(); c++)
00092                 {
00093                     input1gradientptr[c] += thisgradient * input2valueptr[c];
00094                     input2gradientptr[c] += thisgradient * input1valueptr[c];
00095                 }
00096         }
00097 }
00098 
00099 
00100 void ConvolveVariable::symbolicBprop()
00101 { PLERROR("ConvolveVariable::symbolicBprop() not yet implemented"); }
00102 
00103 
00104 
00105 } // end of namespace PLearn
00106 
00107 
00108 /*
00109   Local Variables:
00110   mode:c++
00111   c-basic-offset:4
00112   c-file-style:"stroustrup"
00113   c-file-offsets:((innamespace . 0)(inline-open . 0))
00114   indent-tabs-mode:nil
00115   fill-column:79
00116   End:
00117 */
00118 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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