PLearn 0.1
LogaddOnBagsModule.cc
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00001 // -*- C++ -*-
00002 
00003 // LogaddOnBagsModule.cc
00004 //
00005 // Copyright (C) 2008 Jerome Louradour
00006 //
00007 // Redistribution and use in source and binary forms, with or without
00008 // modification, are permitted provided that the following conditions are met:
00009 //
00010 //  1. Redistributions of source code must retain the above copyright
00011 //     notice, this list of conditions and the following disclaimer.
00012 //
00013 //  2. Redistributions in binary form must reproduce the above copyright
00014 //     notice, this list of conditions and the following disclaimer in the
00015 //     documentation and/or other materials provided with the distribution.
00016 //
00017 //  3. The name of the authors may not be used to endorse or promote
00018 //     products derived from this software without specific prior written
00019 //     permission.
00020 //
00021 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00022 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00023 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00024 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00025 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00026 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00027 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00028 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00029 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00030 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00031 //
00032 // This file is part of the PLearn library. For more information on the PLearn
00033 // library, go to the PLearn Web site at www.plearn.org
00034 
00035 // Author: Jerome Louradour
00036 
00041 #include "LogaddOnBagsModule.h"
00042 
00043 namespace PLearn {
00044 using namespace std;
00045 
00046 PLEARN_IMPLEMENT_OBJECT(
00047     LogaddOnBagsModule,
00048     "For each input i, on a bag of size N, outputs:"
00049        " Logadd([ input_i(1), ..., input_i(N) ]).",
00050     "The 'input' port is typically connected to the output\n"
00051     "port of class activities (input_size = number of classes).\n"
00052     "see OnBagsModule for details on bags.\n");
00053 
00054 LogaddOnBagsModule::LogaddOnBagsModule()
00055 {
00056     output_size = -1;
00057 }
00058 
00059 void LogaddOnBagsModule::declareOptions(OptionList& ol)
00060 {
00061     inherited::declareOptions(ol);
00062 
00063     redeclareOption(ol, "output_size", &LogaddOnBagsModule::output_size,
00064                   OptionBase::learntoption,
00065                   "Size of the 'output' port (same as 'input').");
00066 }
00067 
00068 void LogaddOnBagsModule::build_()
00069 {
00070     PLASSERT( input_size > 0 );
00071     output_size = input_size;
00072     accumulated_output.resize(output_size);
00073     inherited::build();
00074 }
00075 
00076 void LogaddOnBagsModule::build()
00077 {
00078     inherited::build();
00079     build_();
00080 }
00081 
00082 void LogaddOnBagsModule::makeDeepCopyFromShallowCopy(CopiesMap& copies)
00083 {
00084     inherited::makeDeepCopyFromShallowCopy(copies);
00085     deepCopyField(accumulated_output, copies);
00086 }
00087 
00089 // fprop //
00091 
00092 void LogaddOnBagsModule::fpropInit(const Vec& input)
00093 {
00094     accumulated_output << input;
00095 }
00096 void LogaddOnBagsModule::fpropAcc(const Vec& input)
00097 {
00098     for( int i = 0; i < input_size; i++ )
00099         accumulated_output[i] = logadd(accumulated_output[i],
00100                                        input[i]);
00101 }
00102 void LogaddOnBagsModule::fpropOutput(Vec& output)
00103 {
00104     output.resize( output_size );
00105     output << accumulated_output;
00106 }
00107 
00109 // bpropUpdate //
00111 
00112 void LogaddOnBagsModule::bprop( const Mat& baginputs,
00113                                 const Vec& bagoutput_gradient,
00114                                 Mat& baginputs_gradients)
00115 {
00116     int nsamples = baginputs.length();
00117     baginputs_gradients.resize( nsamples, input_size);
00118     for( int i = 0; i < input_size; i++ )
00119     {
00120         Vec tmp_input_gradient;
00121         tmp_input_gradient.resize( nsamples );
00122         softmax( baginputs.column(i).toVecCopy() ,
00123                  tmp_input_gradient );
00124         tmp_input_gradient *= bagoutput_gradient[i];
00125         baginputs_gradients.column(i) << tmp_input_gradient;
00126     }
00127 }
00128 
00129 } // end of namespace PLearn
00130 
00131 
00132 /*
00133   Local Variables:
00134   mode:c++
00135   c-basic-offset:4
00136   c-file-style:"stroustrup"
00137   c-file-offsets:((innamespace . 0)(inline-open . 0))
00138   indent-tabs-mode:nil
00139   fill-column:79
00140   End:
00141 */
00142 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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