PLearn 0.1
EntropyContrastLearner.h
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00001 // -*- C++ -*-
00002 
00003 // EntropyContrastLearner.h
00004 //
00005 // Copyright (C) 2004 Marius Muja 
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: EntropyContrastLearner.h 6863 2007-04-09 20:15:52Z saintmlx $ 
00037  ******************************************************* */
00038 
00039 // Authors: Marius Muja
00040 
00044 #ifndef EntropyContrastLearner_INC
00045 #define EntropyContrastLearner_INC
00046 
00047 #include <plearn_learners/generic/PLearner.h>
00048 #include <plearn/opt/Optimizer.h>
00049 #include "plearn/var/Var_all.h"
00050 
00051 namespace PLearn {
00052 using namespace std;
00053 
00054 class EntropyContrastLearner: public PLearner
00055 {
00056 private:
00057 
00058     typedef PLearner inherited;
00059 
00060 protected:
00061 
00062     // *********************
00063     // * protected options *
00064     // *********************
00065 
00066     Var x;
00067     Var x_hat;
00068     VarArray V;
00069     VarArray W;
00070     VarArray V_b;
00071     VarArray W_b;
00072 
00073     Vec V_save;
00074     Vec V_b_save;
00075     Vec W_save;
00076     Vec W_b_save;
00077         
00078     VarArray g;
00079     Var mu, sigma;
00080     Var mu_hat, sigma_hat;
00081     Var training_cost;
00082     VarArray costs;
00083     Var f;
00084     Var f_hat;
00085 
00086     VarArray params; 
00087 
00088     Func f_output;
00089 
00090 public:
00091 
00092     // ************************
00093     // * public build options *
00094     // ************************
00095 
00096     string distribution;
00097     int nconstraints; 
00098     int nhidden; 
00099     PP<Optimizer> optimizer; // the optimizer to use (no default)
00100     real weight_real;
00101     real weight_generated;
00102     real weight_extra;
00103     real weight_decay_hidden;
00104     real weight_decay_output;
00105     bool normalize_constraints;
00106     bool save_best_params;
00107     real sigma_generated;
00108     real sigma_min_threshold;
00109     real eps;
00110     Vec gradient_scaling;
00111     bool save_x_hat;
00112     string gen_method;
00113     bool use_sigma_min_threshold;
00114 
00115     // ****************
00116     // * Constructors *
00117     // ****************
00118 
00120     // (Make sure the implementation in the .cc
00121     // initializes all fields to reasonable default values)
00122     EntropyContrastLearner();
00123 
00124 
00125     // ********************
00126     // * PLearner methods *
00127     // ********************
00128 
00129 private: 
00130 
00132     // (Please implement in .cc)
00133     void build_();
00134 
00135 protected: 
00136 
00138     // (Please implement in .cc)
00139     static void declareOptions(OptionList& ol);
00140 
00141 public:
00142 
00143     // ************************
00144     // **** Object methods ****
00145     // ************************
00146 
00148     virtual void build();
00149 
00151     virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies);
00152 
00153     // Declares other standard object methods.
00154     // If your class is not instantiatable (it has pure virtual methods)
00155     // you should replace this by PLEARN_DECLARE_ABSTRACT_OBJECT.
00156     PLEARN_DECLARE_OBJECT(EntropyContrastLearner);
00157 
00158 
00159     // **************************
00160     // **** PLearner methods ****
00161     // **************************
00162 
00163 
00164     virtual void initializeParams();
00165 
00168     // (PLEASE IMPLEMENT IN .cc)
00169     virtual int outputsize() const;
00170 
00173     // (PLEASE IMPLEMENT IN .cc)
00174     virtual void forget();
00175 
00176 
00179     // (PLEASE IMPLEMENT IN .cc)
00180     virtual void train();
00181 
00182 
00184     // (PLEASE IMPLEMENT IN .cc)
00185     virtual void computeOutput(const Vec& input, Vec& output) const;
00186 
00188     // (PLEASE IMPLEMENT IN .cc)
00189     virtual void computeCostsFromOutputs(const Vec& input, const Vec& output, 
00190                                          const Vec& target, Vec& costs) const;
00191 
00192 
00194     // (PLEASE IMPLEMENT IN .cc)
00195     virtual TVec<string> getTestCostNames() const;
00196 
00199     // (PLEASE IMPLEMENT IN .cc)
00200     virtual TVec<string> getTrainCostNames() const;
00201 
00202 
00203     // *** SUBCLASS WRITING: ***
00204     // While in general not necessary, in case of particular needs 
00205     // (efficiency concerns for ex) you may also want to overload
00206     // some of the following methods:
00207     // virtual void computeOutputAndCosts(const Vec& input, const Vec& target, Vec& output, Vec& costs) const;
00208     // virtual void computeCostsOnly(const Vec& input, const Vec& target, Vec& costs) const;
00209     // virtual void test(VMat testset, PP<VecStatsCollector> test_stats, VMat testoutputs=0, VMat testcosts=0) const;
00210     // virtual int nTestCosts() const;
00211     // virtual int nTrainCosts() const;
00212     // virtual void resetInternalState();
00213     // virtual bool isStatefulLearner() const;
00214 
00215 };
00216 
00217 // Declares a few other classes and functions related to this class.
00218 DECLARE_OBJECT_PTR(EntropyContrastLearner);
00219 
00220 } // end of namespace PLearn
00221 
00222 #endif
00223 
00224 
00225 /*
00226   Local Variables:
00227   mode:c++
00228   c-basic-offset:4
00229   c-file-style:"stroustrup"
00230   c-file-offsets:((innamespace . 0)(inline-open . 0))
00231   indent-tabs-mode:nil
00232   fill-column:79
00233   End:
00234 */
00235 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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