PLearn 0.1
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00001 // -*- C++ -*- 00002 00003 // PLearn (A C++ Machine Learning Library) 00004 // Copyright (C) 1998 Pascal Vincent 00005 // Copyright (C) 2005 Yoshua Bengio 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 /* ******************************************************* 00037 * $Id: FNetLayerVariable.h 3994 2005-08-25 13:35:03Z chapados $ 00038 * This file is part of the PLearn library. 00039 ******************************************************* */ 00040 00041 #ifndef FNetLayerVariable_INC 00042 #define FNetLayerVariable_INC 00043 00044 #include "NaryVariable.h" 00045 00046 namespace PLearn { 00047 using namespace std; 00048 00049 00054 class FNetLayerVariable: public NaryVariable 00055 { 00056 typedef NaryVariable inherited; 00057 00059 Mat mu; // [hidden unit, input element] centering normalization 00060 Mat invs; // 1/sqrt(mu2 - mu*mu) for normalization 00061 real gradient_threshold; // threshold for |dC/da[k,i]| to 'activate' gradient propagation through unit i at example k 00062 00064 Mat mu2; // to compute invs, the inverse of the standard deviation 00065 real avg_act_gradient; // mov. avg of |dC/da[i,k]| 00066 bool no_bprop_has_been_done; // have we ever done a bprop before? 00067 TVec<Mat> u; // normalized input [example index in minibatch](hidden unit, input index) 00068 Mat inh; // inhibitory signal on each hidden unit (minibatch_size x n_hidden) 00069 Mat cum_inh; 00070 00071 public: 00072 00074 real c1_; 00075 real c2_; 00076 int n_inputs; 00077 int n_hidden; 00078 int minibatch_size; 00079 bool inhibit_next_units; 00080 bool inhibit_by_sum; 00081 bool squashed_inhibition; 00082 bool normalize_inputs; 00083 bool backprop_to_inputs; 00084 real exp_moving_average_coefficient; 00085 real average_error_fraction_to_threshold; 00086 real min_stddev; 00087 00089 FNetLayerVariable(); 00090 00091 FNetLayerVariable(Var inputs, Var weights, 00092 Var biases, Var inhibition_weights, 00093 bool _inhibit_next_units=true, 00094 bool _normalize_inputs=true, 00095 bool _backprop_to_inputs=false, 00096 real _exp_moving_average_coefficient=0.001, 00097 real _average_error_fraction_to_threshold=0.5); 00098 00099 PLEARN_DECLARE_OBJECT(FNetLayerVariable); 00100 00101 virtual void build(); 00102 00103 virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies); 00104 00105 virtual void recomputeSize(int& l, int& w) const; 00106 virtual void fprop(); 00107 virtual void bprop(); 00108 00109 protected: 00110 00111 static void declareOptions(OptionList &ol); 00112 00113 private: 00114 00115 void build_(); 00116 00117 }; 00118 00119 DECLARE_OBJECT_PTR(FNetLayerVariable); 00120 00121 } // end of namespace PLearn 00122 00123 #endif 00124 00125 00126 /* 00127 Local Variables: 00128 mode:c++ 00129 c-basic-offset:4 00130 c-file-style:"stroustrup" 00131 c-file-offsets:((innamespace . 0)(inline-open . 0)) 00132 indent-tabs-mode:nil 00133 fill-column:79 00134 End: 00135 */ 00136 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :