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PlusColumnVariable.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: PlusColumnVariable.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 "PlusColumnVariable.h" 00044 #include "RowSumVariable.h" 00045 00046 namespace PLearn { 00047 using namespace std; 00048 00049 00052 PLEARN_IMPLEMENT_OBJECT(PlusColumnVariable, 00053 "Adds a single-column var to each column of a matrix var", 00054 "NO HELP"); 00055 00056 PlusColumnVariable::PlusColumnVariable(Variable* input1, Variable* input2) 00057 : inherited(input1, input2, input1->length(), input1->width()) 00058 { 00059 build_(); 00060 } 00061 00062 void 00063 PlusColumnVariable::build() 00064 { 00065 inherited::build(); 00066 build_(); 00067 } 00068 00069 void 00070 PlusColumnVariable::build_() 00071 { 00072 if (input1 && input2) { 00073 if(!input2->isColumnVec()) 00074 PLERROR("IN PlusColumnVariable: input2 is not a column"); 00075 if(input2->length() != input1->length()) 00076 PLERROR("IN PlusColumnVariable: input1 and input2 have a different length()"); 00077 } 00078 } 00079 00080 00081 void PlusColumnVariable::recomputeSize(int& l, int& w) const 00082 { 00083 if (input1) { 00084 l = input1->length(); 00085 w = input1->width(); 00086 } else 00087 l = w = 0; 00088 } 00089 00090 00091 void PlusColumnVariable::fprop() 00092 { 00093 int k=0; 00094 for(int i=0; i<length(); i++) 00095 for(int j=0; j<width(); j++, k++) 00096 valuedata[k] = input1->valuedata[k] + input2->valuedata[i]; 00097 } 00098 00099 00100 void PlusColumnVariable::bprop() 00101 { 00102 int k=0; 00103 for(int i=0; i<length(); i++) 00104 for(int j=0; j<width(); j++, k++) 00105 { 00106 input1->gradientdata[k] += gradientdata[k]; 00107 input2->gradientdata[i] += gradientdata[k]; 00108 } 00109 } 00110 00111 00112 void PlusColumnVariable::bbprop() 00113 { 00114 if (input1->diaghessian.length()==0) 00115 input1->resizeDiagHessian(); 00116 if (input2->diaghessian.length()==0) 00117 input2->resizeDiagHessian(); 00118 int k=0; 00119 for(int i=0; i<length(); i++) 00120 for(int j=0; j<width(); j++, k++) 00121 { 00122 input1->diaghessiandata[k] += diaghessiandata[k]; 00123 input2->diaghessiandata[i] += diaghessiandata[k]; 00124 } 00125 } 00126 00127 00128 void PlusColumnVariable::symbolicBprop() 00129 { 00130 input1->accg(g); 00131 input2->accg(rowSum(g)); 00132 } 00133 00134 00135 void PlusColumnVariable::rfprop() 00136 { 00137 if (rValue.length()==0) resizeRValue(); 00138 int k=0; 00139 for(int i=0; i<length(); i++) 00140 for(int j=0; j<width(); j++, k++) 00141 rvaluedata[k] = input1->rvaluedata[k] + input2->rvaluedata[i]; 00142 } 00143 00144 00145 00146 } // end of namespace PLearn 00147 00148

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