PLearn 0.1
|
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 // Copyright (C) 2003 Olivier Delalleau 00009 00010 // Redistribution and use in source and binary forms, with or without 00011 // modification, are permitted provided that the following conditions are met: 00012 // 00013 // 1. Redistributions of source code must retain the above copyright 00014 // notice, this list of conditions and the following disclaimer. 00015 // 00016 // 2. Redistributions in binary form must reproduce the above copyright 00017 // notice, this list of conditions and the following disclaimer in the 00018 // documentation and/or other materials provided with the distribution. 00019 // 00020 // 3. The name of the authors may not be used to endorse or promote 00021 // products derived from this software without specific prior written 00022 // permission. 00023 // 00024 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR 00025 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES 00026 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN 00027 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, 00028 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED 00029 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 00030 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF 00031 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 00032 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 00033 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00034 // 00035 // This file is part of the PLearn library. For more information on the PLearn 00036 // library, go to the PLearn Web site at www.plearn.org 00037 00038 00039 /* ******************************************************* 00040 * $Id: MarginPerceptronCostVariable.cc 3994 2005-08-25 13:35:03Z chapados $ 00041 * This file is part of the PLearn library. 00042 ******************************************************* */ 00043 00044 #include "MarginPerceptronCostVariable.h" 00045 00046 namespace PLearn { 00047 using namespace std; 00048 00051 PLEARN_IMPLEMENT_OBJECT( 00052 MarginPerceptronCostVariable, 00053 "Compute sigmoid of its first input, and then computes the negative " 00054 "cross-entropy cost", 00055 "NO HELP"); 00056 00058 // MarginPerceptronCostVariable // 00060 00061 MarginPerceptronCostVariable::MarginPerceptronCostVariable() 00062 : margin(0.) 00063 { } 00064 00065 MarginPerceptronCostVariable::MarginPerceptronCostVariable(Variable* output, Variable* target, real m) 00066 : inherited(output,target,1,1),margin(m) 00067 { 00068 build_(); 00069 } 00070 00071 void 00072 MarginPerceptronCostVariable::build() 00073 { 00074 inherited::build(); 00075 build_(); 00076 } 00077 00078 void 00079 MarginPerceptronCostVariable::build_() 00080 { 00081 // input2 is target from constructor 00082 if (input2 && input2->size() != 1) 00083 PLERROR("In MarginPerceptronCostVariable: target represents a class (0...n_classes-1) and must be a single integer"); 00084 } 00085 00086 void 00087 MarginPerceptronCostVariable::declareOptions(OptionList &ol) 00088 { 00089 declareOption(ol, "margin", &MarginPerceptronCostVariable::margin, OptionBase::buildoption, ""); 00090 inherited::declareOptions(ol); 00091 } 00092 00094 // recomputeSize // 00096 void MarginPerceptronCostVariable::recomputeSize(int& l, int& w) const 00097 { l=1, w=1; } 00098 00100 // fprop // 00102 void MarginPerceptronCostVariable::fprop() 00103 { 00104 real cost = 0.0; 00105 int target = int(input2->valuedata[0]); 00106 for (int i=0; i<input1->size(); i++) 00107 { 00108 real output = input1->valuedata[i]; 00109 int signed_target = input1->size()==1?target*2-1:(target==i) - (target!=i); 00110 real diff = margin - signed_target * output; 00111 if (diff>0) 00112 cost += diff; 00113 } 00114 valuedata[0] = cost; 00115 } 00116 00118 // bprop // 00120 void MarginPerceptronCostVariable::bprop() 00121 { 00122 real gr = *gradientdata; 00123 int target = int(input2->valuedata[0]); 00124 for (int i=0; i<input1->size(); i++) 00125 { 00126 real output = input1->valuedata[i]; 00127 int signed_target = input1->size()==1?target*2-1:(target==i) - (target!=i); 00128 real diff = margin - signed_target * output; 00129 if (diff>0) 00130 input1->gradientdata[i] -= gr*signed_target; 00131 } 00132 } 00133 00134 } // end of namespace PLearn 00135 00136 00137 /* 00138 Local Variables: 00139 mode:c++ 00140 c-basic-offset:4 00141 c-file-style:"stroustrup" 00142 c-file-offsets:((innamespace . 0)(inline-open . 0)) 00143 indent-tabs-mode:nil 00144 fill-column:79 00145 End: 00146 */ 00147 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :