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MinusRowVariable.cc

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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: MinusRowVariable.cc,v 1.6 2004/04/27 15:58:16 morinf Exp $ 00040 * This file is part of the PLearn library. 00041 ******************************************************* */ 00042 00043 #include "ColumnSumVariable.h" 00044 #include "MinusRowVariable.h" 00045 #include "Var_operators.h" 00046 //#include "Var_utils.h" 00047 00048 namespace PLearn { 00049 using namespace std; 00050 00051 00054 PLEARN_IMPLEMENT_OBJECT(MinusRowVariable, 00055 "ONE LINE DESCR", 00056 "NO HELP"); 00057 00058 MinusRowVariable::MinusRowVariable(Variable* input1, Variable* input2) 00059 : inherited(input1, input2, input1->length(), input1->width()) 00060 { 00061 build_(); 00062 } 00063 00064 void 00065 MinusRowVariable::build() 00066 { 00067 inherited::build(); 00068 build_(); 00069 } 00070 00071 void 00072 MinusRowVariable::build_() 00073 { 00074 if (input1 && input2) { 00075 if(!input2->isRowVec()) 00076 PLERROR("IN MinusRowVariable: input2 is not a row"); 00077 if(input2->width() != input1->width()) 00078 PLERROR("IN MinusRowVariable: input1 and input2 have a different width()"); 00079 } 00080 } 00081 00082 00083 void MinusRowVariable::recomputeSize(int& l, int& w) const 00084 { 00085 if (input1) { 00086 l = input1->length(); 00087 w = input1->width(); 00088 } else 00089 l = w = 0; 00090 } 00091 00092 void MinusRowVariable::fprop() 00093 { 00094 int k=0; 00095 for(int i=0; i<length(); i++) 00096 for(int j=0; j<width(); j++, k++) 00097 valuedata[k] = input1->valuedata[k] - input2->valuedata[j]; 00098 } 00099 00100 00101 void MinusRowVariable::bprop() 00102 { 00103 int k=0; 00104 for(int i=0; i<length(); i++) 00105 for(int j=0; j<width(); j++, k++) 00106 { 00107 input1->gradientdata[k] += gradientdata[k]; 00108 input2->gradientdata[j] -= gradientdata[k]; 00109 } 00110 } 00111 00112 00113 void MinusRowVariable::bbprop() 00114 { 00115 if (input1->diaghessian.length()==0) 00116 input1->resizeDiagHessian(); 00117 if (input2->diaghessian.length()==0) 00118 input2->resizeDiagHessian(); 00119 int k=0; 00120 for(int i=0; i<length(); i++) 00121 for(int j=0; j<width(); j++, k++) 00122 { 00123 input1->diaghessiandata[k] += diaghessiandata[k]; 00124 input2->diaghessiandata[j] -= diaghessiandata[k]; 00125 } 00126 } 00127 00128 00129 void MinusRowVariable::symbolicBprop() 00130 { 00131 input1->accg(g); 00132 input2->accg(-columnSum(g)); 00133 } 00134 00135 00136 00137 } // end of namespace PLearn 00138 00139

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