PLearn 0.1
DEPRECATED/RBMMultinomialLayer.cc
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00001 // -*- C++ -*-
00002 
00003 // RBMMultinomialLayer.cc
00004 //
00005 // Copyright (C) 2006 Pascal Lamblin & Dan Popovici
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 // Authors: Pascal Lamblin & Dan Popovici
00036 
00039 #include "RBMMultinomialLayer.h"
00040 #include <plearn/math/TMat_maths.h>
00041 #include "RBMParameters.h"
00042 
00043 namespace PLearn {
00044 using namespace std;
00045 
00046 PLEARN_IMPLEMENT_OBJECT(
00047     RBMMultinomialLayer,
00048     "Layer in an RBM, consisting in one multinomial unit",
00049     "");
00050 
00051 RBMMultinomialLayer::RBMMultinomialLayer()
00052 {
00053 }
00054 
00055 RBMMultinomialLayer::RBMMultinomialLayer( int the_size )
00056 {
00057     size = the_size;
00058     units_types = string( the_size, 'l' );
00059     activations.resize( the_size );
00060     sample.resize( the_size );
00061     expectation.resize( the_size );
00062     expectation_is_up_to_date = false;
00063 }
00064 
00067 void RBMMultinomialLayer::getUnitActivations( int i, PP<RBMParameters> rbmp,
00068                                               int offset )
00069 {
00070     Vec activation = activations.subVec( i, 1 );
00071     rbmp->computeUnitActivations( i+offset, 1, activation );
00072     expectation_is_up_to_date = false;
00073 }
00074 
00075 void RBMMultinomialLayer::getAllActivations( PP<RBMParameters> rbmp,
00076                                              int offset )
00077 {
00078     rbmp->computeUnitActivations( offset, size, activations );
00079     expectation_is_up_to_date = false;
00080 }
00081 
00082 void RBMMultinomialLayer::generateSample()
00083 {
00084     computeExpectation();
00085 
00086     int i = random_gen->multinomial_sample( expectation );
00087     fill_one_hot( sample, i, 0., 1. );
00088 }
00089 
00090 void RBMMultinomialLayer::computeExpectation()
00091 {
00092     if( expectation_is_up_to_date )
00093         return;
00094 
00095     // expectation = softmax(-activations)
00096     softmaxMinus(activations, expectation);
00097     expectation_is_up_to_date = true;
00098 }
00099 
00100 void RBMMultinomialLayer::bpropUpdate(const Vec& input, const Vec& output,
00101                                       Vec& input_gradient,
00102                                       const Vec& output_gradient)
00103 {
00104     PLERROR( "RBMMultinomialLayer::bpropUpdate not implemented yet." );
00105 }
00106 
00107 
00108 void RBMMultinomialLayer::declareOptions(OptionList& ol)
00109 {
00110 /*
00111     declareOption(ol, "size", &RBMMultinomialLayer::size,
00112                   OptionBase::buildoption,
00113                   "Number of units.");
00114 */
00115     // Now call the parent class' declareOptions
00116     inherited::declareOptions(ol);
00117 }
00118 
00119 void RBMMultinomialLayer::build_()
00120 {
00121     if( size < 0 )
00122         size = int(units_types.size());
00123     if( size != (int) units_types.size() )
00124         units_types = string( size, 'l' );
00125 
00126     activations.resize( size );
00127     sample.resize( size );
00128     expectation.resize( size );
00129     expectation_is_up_to_date = false;
00130 }
00131 
00132 void RBMMultinomialLayer::build()
00133 {
00134     inherited::build();
00135     build_();
00136 }
00137 
00138 
00139 void RBMMultinomialLayer::makeDeepCopyFromShallowCopy(CopiesMap& copies)
00140 {
00141     inherited::makeDeepCopyFromShallowCopy(copies);
00142 }
00143 
00144 
00145 } // end of namespace PLearn
00146 
00147 
00148 /*
00149   Local Variables:
00150   mode:c++
00151   c-basic-offset:4
00152   c-file-style:"stroustrup"
00153   c-file-offsets:((innamespace . 0)(inline-open . 0))
00154   indent-tabs-mode:nil
00155   fill-column:79
00156   End:
00157 */
00158 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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