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) 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: DotProductVariable.cc 7068 2007-05-11 22:15:15Z simonl $ 00040 * This file is part of the PLearn library. 00041 ******************************************************* */ 00042 00043 #include "DotProductVariable.h" 00044 #include "Var_operators.h" 00045 //#include "Var_utils.h" 00046 00047 namespace PLearn { 00048 using namespace std; 00049 00050 00053 // Dot product between 2 matrices (or vectors) with same number of elements 00054 00055 PLEARN_IMPLEMENT_OBJECT(DotProductVariable, 00056 "Dot product between 2 matrices (or vectors) with same number of elements", 00057 "NO HELP"); 00058 00059 DotProductVariable::DotProductVariable(Variable* input1, Variable* input2) 00060 : inherited(input1, input2, 1, 1) 00061 { 00062 build_(); 00063 } 00064 00065 void 00066 DotProductVariable::build() 00067 { 00068 inherited::build(); 00069 build_(); 00070 } 00071 00072 void 00073 DotProductVariable::build_() 00074 { 00075 if(input1 && input2 && (input1->nelems() != input2->nelems())) 00076 PLERROR("IN DotProductVariable input1 and input2 must have the " 00077 "same number of elements: %dx%d != %dx%d", 00078 input1->length(), input1->width(), input2->length(), input2->width()); 00079 } 00080 00081 void DotProductVariable::recomputeSize(int& l, int& w) const 00082 { l=1; w=1; } 00083 00084 00085 00086 00087 00088 00089 00090 00091 void DotProductVariable::fprop() 00092 { 00093 real sum = 0.0; 00094 for (int k=0; k<input1->nelems(); k++) 00095 sum += input1->valuedata[k] * input2->valuedata[k]; 00096 valuedata[0] = sum; 00097 } 00098 00099 00100 void DotProductVariable::bprop() 00101 { 00102 real grad = gradientdata[0]; 00103 for (int k=0; k<input1->nelems(); k++) 00104 { 00105 input1->gradientdata[k] += input2->valuedata[k] * grad; 00106 input2->gradientdata[k] += input1->valuedata[k] * grad; 00107 } 00108 } 00109 00110 00111 void DotProductVariable::bbprop() 00112 { 00113 if (input1->diaghessian.length()==0) 00114 input1->resizeDiagHessian(); 00115 if (input2->diaghessian.length()==0) 00116 input2->resizeDiagHessian(); 00117 real h = diaghessiandata[0]; 00118 for (int k=0; k<input1->nelems(); k++) 00119 { 00120 real in2v=input2->valuedata[k]; 00121 input1->diaghessiandata[k] += in2v * in2v * h; 00122 real in1v=input1->valuedata[k]; 00123 input2->diaghessiandata[k] += in1v * in1v * h; 00124 } 00125 } 00126 00127 00128 void DotProductVariable::symbolicBprop() 00129 { 00130 input1->accg(input2*g); 00131 input2->accg(input1*g); 00132 } 00133 00134 00135 void DotProductVariable::rfprop() 00136 { 00137 if (rValue.length()==0) resizeRValue(); 00138 real sum = 0.0; 00139 for (int k=0; k<input1->nelems(); k++) 00140 sum += input1->rvaluedata[k] * input2->valuedata[k] + input1->valuedata[k] * input2->rvaluedata[k]; 00141 rvaluedata[0] = sum; 00142 } 00143 00144 00145 00146 } // end of namespace PLearn 00147 00148 00149 /* 00150 Local Variables: 00151 mode:c++ 00152 c-basic-offset:4 00153 c-file-style:"stroustrup" 00154 c-file-offsets:((innamespace . 0)(inline-open . 0)) 00155 indent-tabs-mode:nil 00156 fill-column:79 00157 End: 00158 */ 00159 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :