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UnaryHardSlopeVariable.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: UnaryHardSlopeVariable.cc,v 1.2 2004/04/27 16:03:35 morinf Exp $ 00040 * This file is part of the PLearn library. 00041 ******************************************************* */ 00042 00043 #include "UnaryHardSlopeVariable.h" 00044 #include "Var_operators.h" 00045 00046 namespace PLearn { 00047 using namespace std; 00048 00049 00052 PLEARN_IMPLEMENT_OBJECT(UnaryHardSlopeVariable, 00053 "Hard slope function whose Var input is only the argument of the function.", 00054 "Maps x (elementwise) to 0 if x<left, 1 if x>right, and linear in between otherwise."); 00055 00056 UnaryHardSlopeVariable::UnaryHardSlopeVariable(Variable* input,real l,real r) 00057 : inherited(input, input->length(), input->width()) , 00058 left(l), right(r), inv_slope(1.0/(r-l)) 00059 {} 00060 00061 void 00062 UnaryHardSlopeVariable::build() 00063 { 00064 inherited::build(); 00065 build_(); 00066 } 00067 00068 void 00069 UnaryHardSlopeVariable::build_() 00070 { 00071 inv_slope = (1.0 / (right - 1)); 00072 } 00073 00074 void 00075 UnaryHardSlopeVariable::declareOptions(OptionList &ol) 00076 { 00077 declareOption(ol, "left", &UnaryHardSlopeVariable::left, OptionBase::buildoption, ""); 00078 declareOption(ol, "right", &UnaryHardSlopeVariable::right, OptionBase::buildoption, ""); 00079 inherited::declareOptions(ol); 00080 } 00081 00082 void UnaryHardSlopeVariable::recomputeSize(int& l, int& w) const 00083 { 00084 if (input) { 00085 l = input->length(); 00086 w = input->width(); 00087 } else 00088 l = w = 0; 00089 } 00090 00091 00092 void UnaryHardSlopeVariable::fprop() 00093 { 00094 int l = nelems(); 00095 real* inputptr = input->valuedata; 00096 real* ptr = valuedata; 00097 for(int i=0; i<l; i++) 00098 *ptr++ = hard_slope(*inputptr++,left,right); 00099 } 00100 00101 00102 void UnaryHardSlopeVariable::bprop() 00103 { 00104 int l = nelems(); 00105 real* inputgradientptr = input->gradientdata; 00106 real* gradientptr = gradientdata; 00107 real* valueptr = valuedata; 00108 for(int i=0; i<l; i++) 00109 { 00110 real x = *valueptr++; 00111 if (x>left) 00112 if (x<right) 00113 *inputgradientptr++ += *gradientptr++ * inv_slope; 00114 } 00115 } 00116 00117 00118 } // end of namespace PLearn 00119 00120

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