PLearn 0.1
Convolution2DModule.h
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00001 // -*- C++ -*-
00002 
00003 // Convolution2DModule.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 Convolution2DModule_INC
00041 #define Convolution2DModule_INC
00042 
00043 #include <plearn_learners/online/OnlineLearningModule.h>
00044 
00045 namespace PLearn {
00046 
00051 class Convolution2DModule : public OnlineLearningModule
00052 {
00053     typedef OnlineLearningModule inherited;
00054 
00055 public:
00056     //#####  Public Build Options  ############################################
00057 
00060 
00062     int n_input_images;
00063 
00065     int input_images_length;
00066 
00068     int input_images_width;
00069 
00071     int n_output_images;
00072 
00074     int kernel_length;
00075 
00077     int kernel_width;
00078 
00080     int kernel_step1;
00081 
00083     int kernel_step2;
00084 
00090     TMat<int> connection_matrix;
00091 
00093     real start_learning_rate;
00094 
00097     real decrease_constant;
00098 
00099 
00100     //#####  Learnt options, that we would want to access  ####################
00101 
00103     TMat<Mat> kernels;
00104 
00106     Vec bias;
00107 
00108     //#####  Not options  #####################################################
00110     int output_images_length;
00111 
00113     int output_images_width;
00114 
00116     int input_images_size;
00117 
00119     int output_images_size;
00120 
00122     int kernel_size;
00123 
00124 public:
00125     //#####  Public Member Functions  #########################################
00126 
00128     // ### Make sure the implementation in the .cc
00129     // ### initializes all fields to reasonable default values.
00130     Convolution2DModule();
00131 
00132     // Your other public member functions go here
00133 
00135     virtual void fprop(const Vec& input, Vec& output) const;
00136 
00138     virtual void fprop(const TVec<Mat*>& ports_value);
00139 
00150     // virtual void bpropUpdate(const Vec& input, const Vec& output,
00151     //                          const Vec& output_gradient);
00152 
00155     virtual void bpropUpdate(const Vec& input, const Vec& output,
00156                              Vec& input_gradient,
00157                              const Vec& output_gradient,
00158                              bool accumulate=false);
00159 
00161     virtual void bpropAccUpdate(const TVec<Mat*>& ports_value,
00162                                 const TVec<Mat*>& ports_gradient);
00163 
00173     // virtual void bbpropUpdate(const Vec& input, const Vec& output,
00174     //                           const Vec& output_gradient,
00175     //                           const Vec& output_diag_hessian);
00176 
00178     virtual void bbpropUpdate(const Vec& input, const Vec& output,
00179                               Vec& input_gradient,
00180                               const Vec& output_gradient,
00181                               Vec& input_diag_hessian,
00182                               const Vec& output_diag_hessian,
00183                               bool accumulate=false);
00184 
00188     virtual void forget();
00189 
00190 
00195     // virtual void finalize();
00196 
00199     // virtual bool bpropDoesNothing();
00200 
00201     //#####  PLearn::Object Protocol  #########################################
00202 
00203     // Declares other standard object methods.
00204     // ### If your class is not instantiatable (it has pure virtual methods)
00205     // ### you should replace this by PLEARN_DECLARE_ABSTRACT_OBJECT
00206     PLEARN_DECLARE_OBJECT(Convolution2DModule);
00207 
00208     // Simply calls inherited::build() then build_()
00209     virtual void build();
00210 
00212     virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies);
00213 
00214 
00215 protected:
00216     //#####  Protected Member Functions  ######################################
00217 
00219     static void declareOptions(OptionList& ol);
00220 
00221 private:
00222     //#####  Private Member Functions  ########################################
00223 
00225     void build_();
00226 
00228     void build_kernels();
00229 
00230 private:
00231     //#####  Private Data Members  ############################################
00232 
00233     // The rest of the private stuff goes here
00234     real learning_rate;
00235     int step_number;
00236 
00237     // The Mat they contain will point to sub-parts of input and output vectors
00238     // and gradients, for more convenience
00239     TVec<Mat> input_images;
00240     TVec<Mat> output_images;
00241     TVec<Mat> input_gradients;
00242     TVec<Mat> output_gradients;
00243     TVec<Mat> input_diag_hessians;
00244     TVec<Mat> output_diag_hessians;
00245 
00246     // Will store gradients wrt kernels
00247     mutable Mat kernel_gradient;
00248     TMat<Mat> kernel_gradients;
00249 
00250     // Will store the term-to-term squared kernels (for bbprop)
00251     mutable Mat squared_kernel;
00252 
00253     TVec<string> ports;
00254 };
00255 
00256 // Declares a few other classes and functions related to this class
00257 DECLARE_OBJECT_PTR(Convolution2DModule);
00258 
00259 } // end of namespace PLearn
00260 
00261 #endif
00262 
00263 
00264 /*
00265   Local Variables:
00266   mode:c++
00267   c-basic-offset:4
00268   c-file-style:"stroustrup"
00269   c-file-offsets:((innamespace . 0)(inline-open . 0))
00270   indent-tabs-mode:nil
00271   fill-column:79
00272   End:
00273 */
00274 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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