PLearn 0.1
SparseIncrementalAffineTransformVariable.h
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00001 // -*- C++ -*-
00002 
00003 // PLearn (A C++ Machine Learning Library)
00004 // Copyright (C) 1998 Pascal Vincent
00005 // Copyright (C) 1999-2002 Pascal Vincent, Yoshua Bengio, Rejean Ducharme and University of Montreal
00006 // Copyright (C) 2001-2002 Nicolas Chapados, Ichiro Takeuchi, Jean-Sebastien Senecal
00007 // Copyright (C) 2002 Xiangdong Wang, Christian Dorion
00008 
00009 // Redistribution and use in source and binary forms, with or without
00010 // modification, are permitted provided that the following conditions are met:
00011 // 
00012 //  1. Redistributions of source code must retain the above copyright
00013 //     notice, this list of conditions and the following disclaimer.
00014 // 
00015 //  2. Redistributions in binary form must reproduce the above copyright
00016 //     notice, this list of conditions and the following disclaimer in the
00017 //     documentation and/or other materials provided with the distribution.
00018 // 
00019 //  3. The name of the authors may not be used to endorse or promote
00020 //     products derived from this software without specific prior written
00021 //     permission.
00022 // 
00023 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00024 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00025 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00026 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00027 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00028 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00029 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00030 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00031 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00032 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00033 // 
00034 // This file is part of the PLearn library. For more information on the PLearn
00035 // library, go to the PLearn Web site at www.plearn.org
00036 
00037 
00038 /* *******************************************************      
00039    * $Id: SparseIncrementalAffineTransformVariable.h 1442 2004-04-27 15:58:16Z morinf $
00040    * This file is part of the PLearn library.
00041    ******************************************************* */
00042 
00043 #ifndef SparseIncrementalAffineTransformVariable_INC
00044 #define SparseIncrementalAffineTransformVariable_INC
00045 
00046 #include "BinaryVariable.h"
00047 #include <plearn/math/StatsCollector.h>
00048 
00049 namespace PLearn {
00050 using namespace std;
00051 
00052 
00063 class SparseIncrementalAffineTransformVariable: public BinaryVariable
00064 {
00065   typedef BinaryVariable inherited;
00066 
00067 private:
00068   Mat temp_grad;
00069 
00070 protected:
00071   //TVec<TVec<int> > positions;
00072   TVec<StatsCollector> sc_input;
00073   TVec<StatsCollector> sc_grad;
00074   TMat<StatsCollector> sc_input_grad;
00075   Mat positions;
00076   Mat sums;
00077   Vec input_average;
00078   int n_grad_samples;
00079   bool has_seen_input;
00080   int n_weights;
00081 
00082 public:
00083 
00084   int add_n_weights;
00085   real start_grad_prop;
00086   real running_average_prop;
00087 
00089   SparseIncrementalAffineTransformVariable(): add_n_weights(0),  start_grad_prop(1){}
00090   SparseIncrementalAffineTransformVariable(Variable* vec, Variable* transformation, real the_running_average_prop, real the_start_grad_prop);
00091 
00092   PLEARN_DECLARE_OBJECT(SparseIncrementalAffineTransformVariable);
00093 
00094   virtual void build();
00095 
00096   static void declareOptions(OptionList & ol);
00097 
00098   virtual void recomputeSize(int& l, int& w) const;
00099   virtual void fprop();
00100   virtual void bprop();
00101   virtual void symbolicBprop();
00102   virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies);
00103   void reset();
00104 
00105 protected:
00106   void build_();
00107 };
00108 
00109 DECLARE_OBJECT_PTR(SparseIncrementalAffineTransformVariable);
00110 
00112 inline Var sparse_incremental_affine_transform(Var vec, Var transformation, real the_running_average_prop=0.01, real the_start_grad_prop=1)
00113 { 
00114   return new SparseIncrementalAffineTransformVariable(vec,transformation,the_running_average_prop,the_start_grad_prop);
00115 }
00116 
00117 } // end of namespace PLearn
00118 
00119 #endif 
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