PLearn 0.1
TopDownAsymetricDeepNetwork.h
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00001 // -*- C++ -*-
00002 
00003 // TopDownAsymetricDeepNetwork.h
00004 //
00005 // Copyright (C) 2008 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 // Authors: Hugo Larochelle
00036 
00040 #ifndef TopDownAsymetricDeepNetwork_INC
00041 #define TopDownAsymetricDeepNetwork_INC
00042 
00043 #include <plearn/vmat/ClassSubsetVMatrix.h>
00044 #include <plearn_learners/generic/PLearner.h>
00045 #include <plearn_learners/online/GradNNetLayerModule.h>
00046 #include <plearn_learners/online/OnlineLearningModule.h>
00047 #include <plearn_learners/online/CostModule.h>
00048 #include <plearn_learners/online/ModuleStackModule.h>
00049 #include <plearn_learners/online/NLLCostModule.h>
00050 #include <plearn_learners/online/ClassErrorCostModule.h>
00051 #include <plearn_learners/online/CombiningCostsModule.h>
00052 #include <plearn_learners/online/RBMClassificationModule.h>
00053 #include <plearn_learners/online/RBMLayer.h>
00054 #include <plearn_learners/online/RBMMixedLayer.h>
00055 #include <plearn_learners/online/RBMConnection.h>
00056 #include <plearn_learners/online/SoftmaxModule.h>
00057 #include <plearn/misc/PTimer.h>
00058 
00059 namespace PLearn {
00060 
00067 class TopDownAsymetricDeepNetwork : public PLearner
00068 {
00069     typedef PLearner inherited;
00070 
00071 public:
00072     //#####  Public Build Options  ############################################
00073 
00075     real cd_learning_rate;
00076     
00078     real cd_decrease_ct;
00079 
00081     real greedy_learning_rate;
00082 
00086     real greedy_decrease_ct;
00087 
00089     real fine_tuning_learning_rate;
00090 
00093     real fine_tuning_decrease_ct;
00094 
00097     TVec<int> training_schedule;
00098 
00100     TVec< PP<RBMLayer> > layers;
00101 
00103     TVec< PP<RBMLayer> > top_down_layers;
00104 
00106     TVec< PP<RBMConnection> > connections;
00107 
00109     TVec< PP<RBMConnection> > reconstruction_connections;
00110 
00112     int n_classes;
00113 
00115     real output_weights_l1_penalty_factor;
00116 
00118     real output_weights_l2_penalty_factor;
00119 
00122     real fraction_of_masked_inputs;
00123 
00124     //#####  Public Learnt Options  ###########################################
00125 
00127     int n_layers;
00128 
00129 public:
00130     //#####  Public Member Functions  #########################################
00131 
00133     TopDownAsymetricDeepNetwork();
00134 
00135     //#####  PLearner Member Functions  #######################################
00136 
00139     virtual int outputsize() const;
00140 
00144     virtual void forget();
00145 
00149     virtual void train();
00150 
00152     virtual void computeOutput(const Vec& input, Vec& output) const;
00153 
00155     virtual void computeCostsFromOutputs(const Vec& input, const Vec& output,
00156                                          const Vec& target, Vec& costs) const;
00157 
00160     virtual TVec<std::string> getTestCostNames() const;
00161 
00164     virtual TVec<std::string> getTrainCostNames() const;
00165 
00166     void greedyStep( const Vec& input, const Vec& target, int index, 
00167                      Vec train_costs, int stage);
00168 
00169     void fineTuningStep( const Vec& input, const Vec& target,
00170                          Vec& train_costs);
00171 
00172     void computeRepresentation( const Vec& input, 
00173                                 Vec& representation, int layer) const;
00174 
00175     //#####  PLearn::Object Protocol  #########################################
00176 
00177     // Declares other standard object methods.
00178     // ### If your class is not instantiatable (it has pure virtual methods)
00179     // ### you should replace this by PLEARN_DECLARE_ABSTRACT_OBJECT_METHODS
00180     PLEARN_DECLARE_OBJECT(TopDownAsymetricDeepNetwork);
00181 
00182     // Simply calls inherited::build() then build_()
00183     virtual void build();
00184 
00186     // (PLEASE IMPLEMENT IN .cc)
00187     virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies);
00188 
00189 protected:
00190     //#####  Not Options  #####################################################
00191 
00194     mutable TVec<Vec> activations;
00195 
00198     mutable TVec<Vec> expectations;
00199 
00203     mutable TVec<Vec> activation_gradients;
00204 
00208     mutable TVec<Vec> expectation_gradients;
00209 
00211     mutable Vec reconstruction_activations;
00212     
00214     mutable Vec reconstruction_activation_gradients;
00215 
00217     mutable Vec reconstruction_expectation_gradients;
00218 
00220     mutable Vec input_representation;
00221 
00223     mutable Vec masked_autoassociator_input;
00224 
00226     mutable TVec<int> autoassociator_input_indices;
00227 
00229     Vec pos_down_val;
00231     Vec pos_up_val;
00233     Vec neg_down_val;
00235     Vec neg_up_val;
00236 
00238     mutable Vec final_cost_input;
00240     mutable Vec final_cost_value;
00242     mutable Vec final_cost_gradient;
00243 
00245     TVec<int> greedy_stages;
00246 
00249     int currently_trained_layer;
00250 
00252     PP<OnlineLearningModule> final_module;
00253 
00255     PP<CostModule> final_cost;
00256 
00257 protected:
00258     //#####  Protected Member Functions  ######################################
00259 
00261     static void declareOptions(OptionList& ol);
00262 
00263 private:
00264     //#####  Private Member Functions  ########################################
00265 
00267     void build_();
00268 
00269     void build_layers_and_connections();
00270 
00271     void build_output_layer_and_cost();
00272 
00273     void setLearningRate( real the_learning_rate );
00274 
00275 private:
00276     //#####  Private Data Members  ############################################
00277 
00278     // The rest of the private stuff goes here    
00279 };
00280 
00281 // Declares a few other classes and functions related to this class
00282 DECLARE_OBJECT_PTR(TopDownAsymetricDeepNetwork);
00283 
00284 } // end of namespace PLearn
00285 
00286 #endif
00287 
00288 
00289 /*
00290   Local Variables:
00291   mode:c++
00292   c-basic-offset:4
00293   c-file-style:"stroustrup"
00294   c-file-offsets:((innamespace . 0)(inline-open . 0))
00295   indent-tabs-mode:nil
00296   fill-column:79
00297   End:
00298 */
00299 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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