PLearn: SoftSlopeVariable.cc Source File

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: SoftSlopeVariable.cc,v 1.8 2004/04/27 15:59:16 morinf Exp $ 00040 * This file is part of the PLearn library. 00041 ******************************************************* */ 00042 00043 #include "SoftSlopeVariable.h" 00044 //#include "Var_utils.h" 00045 00046 namespace PLearn { 00047 using namespace std; 00048 00049 00053 PLEARN_IMPLEMENT_OBJECT(SoftSlopeVariable, 00054 "This Var computes the soft_slope function", 00055 "The soft_slope function is a soft version of linear by parts function.\n" 00056 "(as smoothness goes to infty). More precisely it converges to a function that is\n" 00057 "0 in [-infty,left], linear in [left,right], and 1 in [right,infty], and continuous\n" 00058 "It is always monotonically increasing wrt x (positive derivative in x).\n" 00059 "If the arguments are vectors than the operation is performed element by element on all of them.\n"); 00060 00061 SoftSlopeVariable:: SoftSlopeVariable(Variable* x, Variable* smoothness, Variable* left, Variable* right, bool tabulated_) 00062 : inherited(VarArray(x,smoothness) & Var(left) & Var(right), 00063 x->length()<left->length()?left->length():x->length(), 00064 x->width()<left->width()?left->width():x->width()), tabulated(tabulated_) 00065 {} 00066 00067 void 00068 SoftSlopeVariable::declareOptions(OptionList &ol) 00069 { 00070 declareOption(ol, "tabulated", &SoftSlopeVariable::tabulated, OptionBase::buildoption, ""); 00071 inherited::declareOptions(ol); 00072 } 00073 00074 void SoftSlopeVariable::recomputeSize(int& l, int& w) const 00075 { 00076 l = 0; 00077 w = 0; 00078 if (varray.size() == 4 && varray[0] && varray[1] && varray[2] && varray[3]) { 00079 for (int i = 0; i < 4; i++) { 00080 if (varray[i]->length() > l) 00081 l = varray[i]->length(); 00082 if (varray[i]->width() > w) 00083 w = varray[i]->width(); 00084 } 00085 for (int i = 0; i < 4; i++) { 00086 if (varray[i]->length() != l || varray[i]->width() != w) { 00087 if (varray[i]->length() != 1 || varray[i]->width() != 1) 00088 PLERROR("Each argument of SoftSlopeVariable should either have the same length/width as the others or length 1"); 00089 } 00090 } 00091 } 00092 } 00093 00094 00095 void SoftSlopeVariable::fprop() 00096 { 00097 int n=nelems(); 00098 int n1=varray[0]->nelems(); 00099 int n2=varray[1]->nelems(); 00100 int n3=varray[2]->nelems(); 00101 int n4=varray[3]->nelems(); 00102 real* x = varray[0]->valuedata; 00103 real* smoothness = varray[1]->valuedata; 00104 real* left = varray[2]->valuedata; 00105 real* right = varray[3]->valuedata; 00106 00107 if (n1==n && n2==n && n3==n && n4==n) 00108 for(int i=0; i<n; i++) 00109 valuedata[i] = tabulated?tabulated_soft_slope(x[i], smoothness[i], left[i], right[i]):soft_slope(x[i], smoothness[i], left[i], right[i]); 00110 else if (n1==1 && n2==n && n3==n && n4==n) 00111 for(int i=0; i<n; i++) 00112 valuedata[i] = tabulated?tabulated_soft_slope(*x, smoothness[i], left[i], right[i]):soft_slope(*x, smoothness[i], left[i], right[i]); 00113 else 00114 { 00115 int m1= n1==1?0:1; 00116 int m2= n2==1?0:1; 00117 int m3= n3==1?0:1; 00118 int m4= n4==1?0:1; 00119 for(int i=0; i<n; i++,x+=m1,smoothness+=m2,left+=m3,right+=m4) 00120 valuedata[i] = tabulated?tabulated_soft_slope(*x, *smoothness, *left, *right):soft_slope(*x, *smoothness, *left, *right); 00121 } 00122 } 00123 00124 00125 void SoftSlopeVariable::bprop() 00126 { 00127 int n=nelems(); 00128 int n1=varray[0]->nelems(); 00129 int n2=varray[1]->nelems(); 00130 int n3=varray[2]->nelems(); 00131 int n4=varray[3]->nelems(); 00132 int m1= n1==1?0:1; 00133 int m2= n2==1?0:1; 00134 int m3= n3==1?0:1; 00135 int m4= n4==1?0:1; 00136 real* x = varray[0]->valuedata; 00137 real* smoothness = varray[1]->valuedata; 00138 real* left = varray[2]->valuedata; 00139 real* right = varray[3]->valuedata; 00140 real* dx = varray[0]->gradientdata; 00141 real* dsmoothness = varray[1]->gradientdata; 00142 real* dleft = varray[2]->gradientdata; 00143 real* dright = varray[3]->gradientdata; 00144 for(int i=0; i<n; i++,x+=m1,smoothness+=m2,left+=m3,right+=m4,dx+=m1,dsmoothness+=m2,dleft+=m3,dright+=m4) 00145 { 00146 if (*smoothness == 0) continue; 00147 real inv_smoothness = 1.0 / *smoothness; 00148 real t1 = sigmoid(- *smoothness*(*x-*left)); 00149 real t2 = sigmoid(- *smoothness*(*x-*right)); 00150 real inv_delta=1.0/(*right-*left); 00151 real rat = (tabulated?tabulated_soft_slope(*x, *smoothness, *left, *right):soft_slope(*x, *smoothness, *left, *right)) -1; 00152 real move = rat * inv_delta; 00153 real dss = (-t1*(*x-*left) + t2*(*x-*right))*inv_smoothness*inv_delta - rat * inv_smoothness; 00154 real dll = t1*inv_delta*inv_smoothness + move; 00155 real drr = -t2*inv_delta*inv_smoothness - move; 00156 real dxx = (-t1+t2)*inv_delta; 00157 *dx += gradientdata[i] * dxx; 00158 *dsmoothness += gradientdata[i] * dss; 00159 *dleft += gradientdata[i] * dll; 00160 *dright += gradientdata[i] * drr; 00161 } 00162 } 00163 00164 void SoftSlopeVariable::symbolicBprop() 00165 { 00166 PLERROR("SoftSlopeVariable::symbolicBprop() not implemented"); 00167 } 00168 00169 00170 00171 } // end of namespace PLearn 00172 00173