PLearn 0.1
RBMMatrixConnection.h
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00001 // -*- C++ -*-
00002 
00003 // RBMMatrixConnection.h
00004 //
00005 // Copyright (C) 2006 Pascal Lamblin
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
00036 
00040 #ifndef RBMMatrixConnection_INC
00041 #define RBMMatrixConnection_INC
00042 
00043 #include "RBMConnection.h"
00044 
00045 namespace PLearn {
00046 using namespace std;
00047 
00048 
00053 class RBMMatrixConnection: public RBMConnection
00054 {
00055     typedef RBMConnection inherited;
00056 
00057 public:
00058     //#####  Public Build Options  ############################################
00059 
00065     Vec gibbs_ma_schedule;
00066     real gibbs_ma_increment;
00067     real gibbs_initial_ma_coefficient;
00068 
00069     //#####  Learned Options  #################################################
00070 
00072     real L1_penalty_factor;
00073 
00075     real L2_penalty_factor;
00076 
00077     real L2_decrease_constant;
00078     real L2_shift;
00079     string L2_decrease_type;
00080     int L2_n_updates;
00081 
00083     Mat weights;
00084 
00086     real gibbs_ma_coefficient;
00087 
00088 
00089     //#####  Not Options  #####################################################
00090 
00091 
00093     Mat weights_pos_stats;
00094 
00096     Mat weights_neg_stats;
00097 
00099     Mat weights_inc;
00100 
00101 public:
00102     //#####  Public Member Functions  #########################################
00103 
00105     RBMMatrixConnection( real the_learning_rate=0 );
00106 
00107     // Your other public member functions go here
00108 
00110     virtual void accumulatePosStats( const Vec& down_values,
00111                                      const Vec& up_values );
00112 
00113     virtual void accumulatePosStats( const Mat& down_values,
00114                                      const Mat& up_values );
00115 
00117     virtual void accumulateNegStats( const Vec& down_values,
00118                                      const Vec& up_values );
00119 
00120     virtual void accumulateNegStats( const Mat& down_values,
00121                                      const Mat& up_values );
00122 
00124     virtual void update();
00125 
00128     virtual void update( const Vec& pos_down_values,
00129                          const Vec& pos_up_values,
00130                          const Vec& neg_down_values,
00131                          const Vec& neg_up_values );
00132 
00134     virtual void update( const Mat& pos_down_values,
00135                          const Mat& pos_up_values,
00136                          const Mat& neg_down_values,
00137                          const Mat& neg_up_values);
00138 
00139     // neg_stats <-- gibbs_chain_statistics_forgetting_factor * neg_stats
00140     //              +(1-gibbs_chain_statistics_forgetting_factor)
00141     //               * gibbs_neg_up_values'*gibbs_neg_down_values
00142     // delta w = -lrate * ( pos_up_values'*pos_down_values
00143     //                   - ( background_gibbs_update_ratio*neg_stats
00144     //                      +(1-background_gibbs_update_ratio)
00145     //                       * cd_neg_up_values'*cd_neg_down_values))
00146     virtual void updateCDandGibbs( const Mat& pos_down_values,
00147                                    const Mat& pos_up_values,
00148                                    const Mat& cd_neg_down_values,
00149                                    const Mat& cd_neg_up_values,
00150                                    const Mat& gibbs_neg_down_values,
00151                                    const Mat& gibbs_neg_up_values,
00152                                    real background_gibbs_update_ratio);
00153 
00154     // neg_stats <-- gibbs_chain_statistics_forgetting_factor * neg_stats
00155     //              +(1-gibbs_chain_statistics_forgetting_factor)
00156     //               * gibbs_neg_up_values'*gibbs_neg_down_values
00157     // delta w = -lrate * ( pos_up_values'*pos_down_values - neg_stats )
00158     virtual void updateGibbs( const Mat& pos_down_values,
00159                               const Mat& pos_up_values,
00160                               const Mat& gibbs_neg_down_values,
00161                               const Mat& gibbs_neg_up_values );
00162 
00164     virtual void clearStats();
00165 
00169     virtual void computeProduct( int start, int length,
00170                                  const Vec& activations,
00171                                  bool accumulate=false ) const;
00172 
00174     virtual void computeProducts(int start, int length,
00175                                  Mat& activations,
00176                                  bool accumulate=false ) const;
00177 
00188     // virtual void bpropUpdate(const Vec& input, const Vec& output,
00189     //                          const Vec& output_gradient);
00190 
00193     virtual void fprop(const Vec& input, const Mat& rbm_weights,
00194                        Vec& output) const;
00195 
00197     virtual void getAllWeights(Mat& rbm_weights) const;
00198 
00200     virtual void setAllWeights(const Mat& rbm_weights);
00201 
00204     virtual void bpropUpdate(const Vec& input, const Vec& output,
00205                              Vec& input_gradient,
00206                              const Vec& output_gradient,
00207                              bool accumulate=false);
00208 
00209     virtual void bpropUpdate(const Mat& inputs, const Mat& outputs,
00210                              Mat& input_gradients,
00211                              const Mat& output_gradients,
00212                              bool accumulate = false);
00213 
00214     virtual void bpropAccUpdate(const TVec<Mat*>& ports_value,
00215                                 const TVec<Mat*>& ports_gradient);
00216 
00219     virtual void petiteCulotteOlivierUpdate(
00220         const Vec& input, const Mat& rbm_weights,
00221         const Vec& output,
00222         Vec& input_gradient, Mat& rbm_weights_gradient,
00223         const Vec& output_gradient,
00224         bool accumulate = false);
00225 
00228     virtual void petiteCulotteOlivierCD(Mat& weights_gradient,
00229                                         bool accumulate = false);
00230 
00233     virtual void petiteCulotteOlivierCD(const Vec& pos_down_values,
00234                                         const Vec& pos_up_values,
00235                                         const Vec& neg_down_values,
00236                                         const Vec& neg_up_values,
00237                                         Mat& weights_gradient,
00238                                         bool accumulate = false);
00239 
00241     virtual void applyWeightPenalty();
00242 
00244     virtual void addWeightPenalty(Mat weights, Mat weight_gradients);
00245 
00249     virtual void forget();
00250 
00255     // virtual void finalize();
00256 
00258     virtual int nParameters() const;
00259 
00265     virtual Vec makeParametersPointHere(const Vec& global_parameters);
00266 
00267     //#####  PLearn::Object Protocol  #########################################
00268 
00269     // Declares other standard object methods.
00270     PLEARN_DECLARE_OBJECT(RBMMatrixConnection);
00271 
00272     // Simply calls inherited::build() then build_()
00273     virtual void build();
00274 
00276     virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies);
00277 
00278 protected:
00279     //#####  Protected Member Functions  ######################################
00281     static void declareOptions(OptionList& ol);
00282 
00283 private:
00284     //#####  Private Member Functions  ########################################
00285 
00287     void build_();
00288 
00289 private:
00290     //#####  Private Data Members  ############################################
00291 
00292     // The rest of the private stuff goes here
00293 };
00294 
00295 // Declares a few other classes and functions related to this class
00296 DECLARE_OBJECT_PTR(RBMMatrixConnection);
00297 
00298 } // end of namespace PLearn
00299 
00300 #endif
00301 
00302 
00303 /*
00304   Local Variables:
00305   mode:c++
00306   c-basic-offset:4
00307   c-file-style:"stroustrup"
00308   c-file-offsets:((innamespace . 0)(inline-open . 0))
00309   indent-tabs-mode:nil
00310   fill-column:79
00311   End:
00312 */
00313 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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