PLearn 0.1
NonLocalManifoldParzen.h
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00001 // -*- C++ -*-
00002 
00003 // NonLocalManifoldParzen.h
00004 //
00005 // Copyright (C) 2004 Yoshua Bengio & Hugo Larochelle
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 /* *******************************************************
00036  * $Id: NonLocalManifoldParzen.h 8172 2007-10-10 22:41:33Z larocheh $
00037  ******************************************************* */
00038 
00039 // Authors: Yoshua Bengio & Hugo Larochelle
00040 
00044 #ifndef NonLocalManifoldParzen_INC
00045 #define NonLocalManifoldParzen_INC
00046 
00047 #include "UnconditionalDistribution.h"
00048 #include <plearn/io/PStream.h>
00049 #include <plearn_learners/generic/PLearner.h>
00050 #include <plearn/var/Func.h>
00051 #include <plearn/opt/Optimizer.h>
00052 #include <plearn_learners/distributions/PDistribution.h>
00053 #include <plearn/ker/DistanceKernel.h>
00054 
00055 namespace PLearn {
00056 using namespace std;
00057 
00058 class NonLocalManifoldParzen: public UnconditionalDistribution
00059 {
00060 
00061 private:
00062 
00063     typedef UnconditionalDistribution inherited;
00064 
00065 protected:
00066 
00067     // *********************
00068     // * protected options *
00069     // *********************
00070 
00072     int L;
00074     real log_L;
00076     Func cost_of_one_example;
00078     Var x;
00080     Var W, V, muV, snV;
00082     Var tangent_targets;
00085     Var components;
00087     Var mu;
00089     Var sn;
00091     Var sum_nll;
00093     Var min_sig;
00095     Var init_sig;
00097     Func predictor; // predicts everything about the gaussian
00098 
00100     mutable Mat U_temp, F, distances;
00102     mutable Vec mu_temp,sm_temp,sn_temp,diff,z, x_minus_neighbor,
00103         t_row, neighbor_row, log_gauss,t_dist;
00105     mutable TVec<int> t_nn;
00107     mutable DistanceKernel dk;
00108 
00110     mutable Mat Ut_svd, V_svd;
00112     mutable Vec S_svd;
00113 
00115     Mat mus;
00117     Vec sns;
00119     Mat sms;
00121     TVec<Mat> Fs;
00122 
00124     VMat train_set_with_targets;
00126     VMat targets_vmat;
00128     Var totalcost;
00130     int nsamples;
00131 
00133     Vec paramsvalues;
00134 
00135 public:
00136 
00137     // ************************
00138     // * public build options *
00139     // ************************
00140 
00141     // ** General parameters **
00142 
00144     VarArray parameters;
00146     VMat reference_set;
00148     int ncomponents;
00150     int nneighbors;
00152     int nneighbors_density;
00154     bool store_prediction;
00155     
00156     // ** Gaussian kernel options **
00157 
00159     bool learn_mu;
00161     real sigma_init;
00163     real sigma_min;
00165     int mu_nneighbors;
00167     real sigma_threshold_factor;
00169     real svd_threshold;
00170 
00171     // ** Neural network predictor option **
00172 
00174     int nhidden;
00176     real weight_decay;
00178     string penalty_type;
00180     PP<Optimizer> optimizer;
00182     int batch_size;
00183 
00184     // ****************
00185     // * Constructors *
00186     // ****************
00187 
00189     NonLocalManifoldParzen();
00190 
00191     // ********************
00192     // * PLearner methods *
00193     // ********************
00194 
00195 private:
00196 
00198     void build_();
00199 
00200     //void update_reference_set_parameters();
00201 
00205     void knn(const VMat& vm, const Vec& x, const int& k, TVec<int>& neighbors, bool sortk) const;
00206 
00207 protected:
00208 
00210     static void declareOptions(OptionList& ol);
00211 
00212     virtual void initializeParams();
00213 
00214 public:
00215 
00216     // ************************
00217     // **** Object methods ****
00218     // ************************
00219 
00221     virtual void build();
00222 
00225     virtual void forget();
00226 
00228     virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies);
00229 
00230     // Declares other standard object methods.
00231     // If your class is not instantiatable (it has pure virtual methods)
00232     // you should replace this by PLEARN_DECLARE_ABSTRACT_OBJECT_METHODS.
00233     PLEARN_DECLARE_OBJECT(NonLocalManifoldParzen);
00234 
00235     // *******************************
00236     // **** PDistribution methods ****
00237     // *******************************
00238 
00240     virtual real log_density(const Vec& x) const;
00241 
00244     virtual void train();
00245 
00246     /* Not implemented for now
00248     virtual void expectation(Vec& mu) const;
00249 
00251     virtual void variance(Mat& cov) const;
00252 
00254     virtual void generate(Vec& y) const;
00255 
00257     virtual void resetGenerator(long g_seed);
00258     */
00259 
00261     virtual void computeOutput(const Vec& input, Vec& output) const;
00262 
00264     virtual int outputsize() const;
00265 
00266     /* Not needed anymore
00269     virtual int outputsize() const;
00270     */
00271 
00272 
00273     // *** SUBCLASS WRITING: ***
00274     // While in general not necessary, in case of particular needs
00275     // (efficiency concerns for ex) you may also want to overload
00276     // some of the following methods:
00277     // virtual void computeOutputAndCosts(const Vec& input, const Vec& target, Vec& output, Vec& costs) const;
00278     // virtual void computeCostsOnly(const Vec& input, const Vec& target, Vec& costs) const;
00279     // virtual void test(VMat testset, PP<VecStatsCollector> test_stats, VMat testoutputs=0, VMat testcosts=0) const;
00280     // virtual int nTestCosts() const;
00281     // virtual int nTrainCosts() const;
00282 
00283     //Mat getEigenvectors(int j) const;
00284     //Vec getTrainPoint(int j) const;
00285 };
00286 
00287 // Declares a few other classes and functions related to this class.
00288 DECLARE_OBJECT_PTR(NonLocalManifoldParzen);
00289 
00290 } // end of namespace PLearn
00291 
00292 #endif
00293 
00294 
00295 /*
00296   Local Variables:
00297   mode:c++
00298   c-basic-offset:4
00299   c-file-style:"stroustrup"
00300   c-file-offsets:((innamespace . 0)(inline-open . 0))
00301   indent-tabs-mode:nil
00302   fill-column:79
00303   End:
00304 */
00305 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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