/usr/include/trilinos/ROL_ScalarMinimizationLineSearch.hpp is in libtrilinos-rol-dev 12.12.1-5.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 | // @HEADER
// ************************************************************************
//
// Rapid Optimization Library (ROL) Package
// Copyright (2014) Sandia Corporation
//
// Under terms of Contract DE-AC04-94AL85000, there is a non-exclusive
// license for use of this work by or on behalf of the U.S. Government.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// 1. Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the Corporation nor the names of the
// contributors may be used to endorse or promote products derived from
// this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//
// Questions? Contact lead developers:
// Drew Kouri (dpkouri@sandia.gov) and
// Denis Ridzal (dridzal@sandia.gov)
//
// ************************************************************************
// @HEADER
#ifndef ROL_ScalarMinimizationLineSearch_H
#define ROL_ScalarMinimizationLineSearch_H
/** \class ROL::ScalarMinimizationLineSearch
\brief Implements line search methods that attempt to minimize the
scalar function \f$\phi(t) := f(x+ts)\f$.
*/
#include "ROL_LineSearch.hpp"
#include "ROL_BrentsScalarMinimization.hpp"
#include "ROL_BisectionScalarMinimization.hpp"
#include "ROL_GoldenSectionScalarMinimization.hpp"
#include "ROL_ScalarFunction.hpp"
#include "ROL_Bracketing.hpp"
namespace ROL {
template<class Real>
class ScalarMinimizationLineSearch : public LineSearch<Real> {
private:
Teuchos::RCP<Vector<Real> > xnew_;
Teuchos::RCP<Vector<Real> > g_;
Teuchos::RCP<ScalarMinimization<Real> > sm_;
Teuchos::RCP<Bracketing<Real> > br_;
Teuchos::RCP<ScalarFunction<Real> > sf_;
ECurvatureCondition econd_;
Real c1_;
Real c2_;
Real c3_;
int max_nfval_;
class Phi : public ScalarFunction<Real> {
private:
const Teuchos::RCP<Vector<Real> > xnew_;
const Teuchos::RCP<Vector<Real> > g_;
const Teuchos::RCP<const Vector<Real> > x_;
const Teuchos::RCP<const Vector<Real> > s_;
const Teuchos::RCP<Objective<Real> > obj_;
const Teuchos::RCP<BoundConstraint<Real> > con_;
Real ftol_;
void updateIterate(Real alpha) {
xnew_->set(*x_);
xnew_->axpy(alpha,*s_);
if ( con_->isActivated() ) {
con_->project(*xnew_);
}
}
public:
Phi(const Teuchos::RCP<Vector<Real> > &xnew,
const Teuchos::RCP<Vector<Real> > &g,
const Teuchos::RCP<const Vector<Real> > &x,
const Teuchos::RCP<const Vector<Real> > &s,
const Teuchos::RCP<Objective<Real> > &obj,
const Teuchos::RCP<BoundConstraint<Real> > &con)
: xnew_(xnew), g_(g), x_(x), s_(s), obj_(obj), con_(con),
ftol_(std::sqrt(ROL_EPSILON<Real>())) {}
Real value(const Real alpha) {
updateIterate(alpha);
obj_->update(*xnew_);
return obj_->value(*xnew_,ftol_);
}
Real deriv(const Real alpha) {
updateIterate(alpha);
obj_->update(*xnew_);
obj_->gradient(*g_,*xnew_,ftol_);
return s_->dot(g_->dual());
}
};
class LineSearchStatusTest : public ScalarMinimizationStatusTest<Real> {
private:
Teuchos::RCP<ScalarFunction<Real> > phi_;
const Real f0_;
const Real g0_;
const Real c1_;
const Real c2_;
const Real c3_;
const int max_nfval_;
const ECurvatureCondition econd_;
public:
LineSearchStatusTest(const Real f0, const Real g0,
const Real c1, const Real c2, const Real c3,
const int max_nfval, ECurvatureCondition econd,
const Teuchos::RCP<ScalarFunction<Real> > &phi)
: phi_(phi), f0_(f0), g0_(g0), c1_(c1), c2_(c2), c3_(c3),
max_nfval_(max_nfval), econd_(econd) {}
bool check(Real &x, Real &fx, Real &gx,
int &nfval, int &ngval, const bool deriv = false) {
Real one(1), two(2);
bool armijo = (fx <= f0_ + c1_*x*g0_);
// bool itcond = (nfval >= max_nfval_);
bool curvcond = false;
// if (armijo && !itcond) {
if (armijo) {
if (econd_ == CURVATURECONDITION_GOLDSTEIN) {
curvcond = (fx >= f0_ + (one-c1_)*x*g0_);
}
else if (econd_ == CURVATURECONDITION_NULL) {
curvcond = true;
}
else {
if (!deriv) {
gx = phi_->deriv(x); ngval++;
}
if (econd_ == CURVATURECONDITION_WOLFE) {
curvcond = (gx >= c2_*g0_);
}
else if (econd_ == CURVATURECONDITION_STRONGWOLFE) {
curvcond = (std::abs(gx) <= c2_*std::abs(g0_));
}
else if (econd_ == CURVATURECONDITION_GENERALIZEDWOLFE) {
curvcond = (c2_*g0_ <= gx && gx <= -c3_*g0_);
}
else if (econd_ == CURVATURECONDITION_APPROXIMATEWOLFE) {
curvcond = (c2_*g0_ <= gx && gx <= (two*c1_ - one)*g0_);
}
}
}
//return (armijo && curvcond) || itcond;
return (armijo && curvcond);
}
};
public:
// Constructor
ScalarMinimizationLineSearch( Teuchos::ParameterList &parlist,
const Teuchos::RCP<ScalarMinimization<Real> > &sm = Teuchos::null,
const Teuchos::RCP<Bracketing<Real> > &br = Teuchos::null,
const Teuchos::RCP<ScalarFunction<Real> > &sf = Teuchos::null )
: LineSearch<Real>(parlist) {
Real zero(0), p4(0.4), p6(0.6), p9(0.9), oem4(1.e-4), oem10(1.e-10), one(1);
Teuchos::ParameterList &list0 = parlist.sublist("Step").sublist("Line Search");
Teuchos::ParameterList &list = list0.sublist("Line-Search Method");
// Get Bracketing Method
if( br == Teuchos::null ) {
br_ = Teuchos::rcp(new Bracketing<Real>());
}
else {
br_ = br;
}
// Get ScalarMinimization Method
std::string type = list.get("Type","Brent's");
Real tol = list.sublist(type).get("Tolerance",oem10);
int niter = list.sublist(type).get("Iteration Limit",1000);
Teuchos::ParameterList plist;
plist.sublist("Scalar Minimization").set("Type",type);
plist.sublist("Scalar Minimization").sublist(type).set("Tolerance",tol);
plist.sublist("Scalar Minimization").sublist(type).set("Iteration Limit",niter);
if( sm == Teuchos::null ) { // No user-provided ScalarMinimization object
if ( type == "Brent's" ) {
sm_ = Teuchos::rcp(new BrentsScalarMinimization<Real>(plist));
}
else if ( type == "Bisection" ) {
sm_ = Teuchos::rcp(new BisectionScalarMinimization<Real>(plist));
}
else if ( type == "Golden Section" ) {
sm_ = Teuchos::rcp(new GoldenSectionScalarMinimization<Real>(plist));
}
else {
TEUCHOS_TEST_FOR_EXCEPTION(true, std::invalid_argument,
">>> (ROL::ScalarMinimizationLineSearch): Undefined ScalarMinimization type!");
}
}
else {
sm_ = sm;
}
sf_ = sf;
// Status test for line search
econd_ = StringToECurvatureCondition(list0.sublist("Curvature Condition").get("Type","Strong Wolfe Conditions"));
max_nfval_ = list0.get("Function Evaluation Limit",20);
c1_ = list0.get("Sufficient Decrease Tolerance",oem4);
c2_ = list0.sublist("Curvature Condition").get("General Parameter",p9);
c3_ = list0.sublist("Curvature Condition").get("Generalized Wolfe Parameter",p6);
// Check status test inputs
c1_ = ((c1_ < zero) ? oem4 : c1_);
c2_ = ((c2_ < zero) ? p9 : c2_);
c3_ = ((c3_ < zero) ? p9 : c3_);
if ( c2_ <= c1_ ) {
c1_ = oem4;
c2_ = p9;
}
EDescent edesc = StringToEDescent(list0.sublist("Descent Method").get("Type","Quasi-Newton Method"));
if ( edesc == DESCENT_NONLINEARCG ) {
c2_ = p4;
c3_ = std::min(one-c2_,c3_);
}
}
void initialize( const Vector<Real> &x, const Vector<Real> &s, const Vector<Real> &g,
Objective<Real> &obj, BoundConstraint<Real> &con ) {
LineSearch<Real>::initialize(x,s,g,obj,con);
xnew_ = x.clone();
g_ = g.clone();
}
// Find the minimum of phi(alpha) = f(x + alpha*s) using Brent's method
void run( Real &alpha, Real &fval, int &ls_neval, int &ls_ngrad,
const Real &gs, const Vector<Real> &s, const Vector<Real> &x,
Objective<Real> &obj, BoundConstraint<Real> &con ) {
ls_neval = 0; ls_ngrad = 0;
// Get initial line search parameter
alpha = LineSearch<Real>::getInitialAlpha(ls_neval,ls_ngrad,fval,gs,x,s,obj,con);
// Build ScalarFunction and ScalarMinimizationStatusTest
Teuchos::RCP<const Vector<Real> > x_ptr = Teuchos::rcpFromRef(x);
Teuchos::RCP<const Vector<Real> > s_ptr = Teuchos::rcpFromRef(s);
Teuchos::RCP<Objective<Real> > obj_ptr = Teuchos::rcpFromRef(obj);
Teuchos::RCP<BoundConstraint<Real> > bnd_ptr = Teuchos::rcpFromRef(con);
Teuchos::RCP<ScalarFunction<Real> > phi;
if( sf_ == Teuchos::null ) {
phi = Teuchos::rcp(new Phi(xnew_,g_,x_ptr,s_ptr,obj_ptr,bnd_ptr));
}
else {
phi = sf_;
}
Teuchos::RCP<ScalarMinimizationStatusTest<Real> > test
= Teuchos::rcp(new LineSearchStatusTest(fval,gs,c1_,c2_,c3_,max_nfval_,econd_,phi));
// Run Bracketing
int nfval = 0, ngrad = 0;
Real A(0), fA = fval;
Real B = alpha, fB = phi->value(B);
br_->run(alpha,fval,A,fA,B,fB,nfval,ngrad,*phi,*test);
B = alpha;
ls_neval += nfval; ls_ngrad += ngrad;
// Run ScalarMinimization
nfval = 0, ngrad = 0;
sm_->run(fval, alpha, nfval, ngrad, *phi, A, B, *test);
ls_neval += nfval; ls_ngrad += ngrad;
LineSearch<Real>::setNextInitialAlpha(alpha);
}
};
}
#endif
|