/usr/include/trilinos/ROL_lSR1.hpp is in libtrilinos-rol-dev 12.10.1-3.
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 | // @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_LSR1_H
#define ROL_LSR1_H
/** \class ROL::lSR1
\brief Provides definitions for limited-memory SR1 operators.
*/
#include "ROL_Secant.hpp"
#include "ROL_Types.hpp"
namespace ROL {
template<class Real>
class lSR1 : public Secant<Real> {
private:
mutable bool updateIterate_;
bool isInitialized_;
public:
lSR1(int M) : Secant<Real>(M), isInitialized_(false) {
updateIterate_ = true;
}
// Update Secant Approximation
void updateStorage( const Vector<Real> &x, const Vector<Real> &grad,
const Vector<Real> &gp, const Vector<Real> &s,
const Real snorm, const int iter ) {
Real one(1);
// Get Generic Secant State
Teuchos::RCP<SecantState<Real> >& state = Secant<Real>::get_state();
if ( !isInitialized_ ) {
state->iterate = x.clone();
isInitialized_ = true;
}
state->iterate->set(x);
state->iter = iter;
Teuchos::RCP<Vector<Real> > gradDiff = grad.clone();
gradDiff->set(grad);
gradDiff->axpy(-one,gp);
Real sy = s.dot(gradDiff->dual());
if (updateIterate_ || state->current == -1) {
if (state->current < state->storage-1) {
state->current++; // Increment Storage
}
else {
state->iterDiff.erase(state->iterDiff.begin()); // Remove first element of s list
state->gradDiff.erase(state->gradDiff.begin()); // Remove first element of y list
state->product.erase(state->product.begin()); // Remove first element of rho list
}
state->iterDiff.push_back(s.clone());
state->iterDiff[state->current]->set(s); // s=x_{k+1}-x_k
state->gradDiff.push_back(grad.clone());
state->gradDiff[state->current]->set(*gradDiff); // y=g_{k+1}-g_k
state->product.push_back(sy); // ys=1/rho
}
updateIterate_ = true;
}
// Apply Initial Secant Approximate Inverse Hessian
virtual void applyH0( Vector<Real> &Hv, const Vector<Real> &v ) const {
Hv.set(v.dual());
}
// Apply lSR1 Approximate Inverse Hessian
void applyH( Vector<Real> &Hv, const Vector<Real> &v ) const {
// Get Generic Secant State
const Teuchos::RCP<SecantState<Real> >& state = Secant<Real>::get_state();
// Apply initial Hessian approximation to v
applyH0(Hv,v);
std::vector<Teuchos::RCP<Vector<Real> > > a(state->current+1);
std::vector<Teuchos::RCP<Vector<Real> > > b(state->current+1);
Real byi(0), byj(0), bv(0), normbi(0), normyi(0), one(1);
for (int i = 0; i <= state->current; i++) {
// Compute Hy
a[i] = Hv.clone();
applyH0(*(a[i]),*(state->gradDiff[i]));
for (int j = 0; j < i; j++) {
byj = b[j]->dot((state->gradDiff[j])->dual());
byi = b[j]->dot((state->gradDiff[i])->dual());
a[i]->axpy(byi/byj,*(b[j]));
}
// Compute s - Hy
b[i] = Hv.clone();
b[i]->set(*(state->iterDiff[i]));
b[i]->axpy(-one,*(a[i]));
// Compute Hv
byi = b[i]->dot((state->gradDiff[i])->dual());
normbi = b[i]->norm();
normyi = (state->gradDiff[i])->norm();
if ( i == state->current && std::abs(byi) < sqrt(ROL_EPSILON<Real>())*normbi*normyi ) {
updateIterate_ = false;
}
else {
updateIterate_ = true;
bv = b[i]->dot(v.dual());
Hv.axpy(bv/byi,*(b[i]));
}
}
}
// Apply Initial Secant Approximate Hessian
virtual void applyB0( Vector<Real> &Bv, const Vector<Real> &v ) const {
Bv.set(v.dual());
}
// Apply lSR1 Approximate Hessian
void applyB( Vector<Real> &Bv, const Vector<Real> &v ) const {
// Get Generic Secant State
const Teuchos::RCP<SecantState<Real> >& state = Secant<Real>::get_state();
// Apply initial Hessian approximation to v
applyB0(Bv,v);
std::vector<Teuchos::RCP<Vector<Real> > > a(state->current+1);
std::vector<Teuchos::RCP<Vector<Real> > > b(state->current+1);
Real bsi(0), bsj(0), bv(0), normbi(0), normsi(0), one(1);
for (int i = 0; i <= state->current; i++) {
// Compute Hy
a[i] = Bv.clone();
applyB0(*(a[i]),*(state->iterDiff[i]));
for (int j = 0; j < i; j++) {
bsj = (state->iterDiff[j])->dot(b[j]->dual());
bsi = (state->iterDiff[i])->dot(b[j]->dual());
a[i]->axpy(bsi/bsj,*(b[j]));
}
// Compute s - Hy
b[i] = Bv.clone();
b[i]->set(*(state->gradDiff[i]));
b[i]->axpy(-one,*(a[i]));
// Compute Hv
bsi = (state->iterDiff[i])->dot(b[i]->dual());
normbi = b[i]->norm();
normsi = (state->iterDiff[i])->norm();
if ( i == state->current && std::abs(bsi) < sqrt(ROL_EPSILON<Real>())*normbi*normsi ) {
updateIterate_ = false;
}
else {
updateIterate_ = true;
bv = b[i]->dot(v.dual());
Bv.axpy(bv/bsi,*(b[i]));
}
}
}
};
}
#endif
|