ROL
ROL_ProjectedNewtonKrylovStep.hpp
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2 // *****************************************************************************
3 // Rapid Optimization Library (ROL) Package
4 //
5 // Copyright 2014 NTESS and the ROL contributors.
6 // SPDX-License-Identifier: BSD-3-Clause
7 // *****************************************************************************
8 // @HEADER
9 
10 #ifndef ROL_PROJECTEDNEWTONKRYLOVSTEP_H
11 #define ROL_PROJECTEDNEWTONKRYLOVSTEP_H
12 
13 #include "ROL_Types.hpp"
14 #include "ROL_Step.hpp"
15 
16 #include "ROL_Secant.hpp"
17 #include "ROL_KrylovFactory.hpp"
18 #include "ROL_LinearOperator.hpp"
19 
20 #include <sstream>
21 #include <iomanip>
22 
30 namespace ROL {
31 
32 template <class Real>
33 class ProjectedNewtonKrylovStep : public Step<Real> {
34 private:
35 
36  ROL::Ptr<Secant<Real> > secant_;
37  ROL::Ptr<Krylov<Real> > krylov_;
38 
41 
42  ROL::Ptr<Vector<Real> > gp_;
43  ROL::Ptr<Vector<Real> > d_;
44 
47  int verbosity_;
48  const bool computeObj_;
49 
52 
53  std::string krylovName_;
54  std::string secantName_;
55 
56  class HessianPNK : public LinearOperator<Real> {
57  private:
58  const ROL::Ptr<Objective<Real> > obj_;
59  const ROL::Ptr<BoundConstraint<Real> > bnd_;
60  const ROL::Ptr<Vector<Real> > x_;
61  const ROL::Ptr<Vector<Real> > g_;
62  ROL::Ptr<Vector<Real> > v_;
63  Real eps_;
64  public:
65  HessianPNK(const ROL::Ptr<Objective<Real> > &obj,
66  const ROL::Ptr<BoundConstraint<Real> > &bnd,
67  const ROL::Ptr<Vector<Real> > &x,
68  const ROL::Ptr<Vector<Real> > &g,
69  Real eps = 0 )
70  : obj_(obj), bnd_(bnd), x_(x), g_(g), eps_(eps) {
71  v_ = x_->clone();
72  }
73  void apply(Vector<Real> &Hv, const Vector<Real> &v, Real &tol) const {
74  v_->set(v);
75  bnd_->pruneActive(*v_,*g_,*x_,eps_);
76  obj_->hessVec(Hv,*v_,*x_,tol);
77  bnd_->pruneActive(Hv,*g_,*x_,eps_);
78  v_->set(v);
79  bnd_->pruneInactive(*v_,*g_,*x_,eps_);
80  Hv.plus(v_->dual());
81  }
82  };
83 
84  class PrecondPNK : public LinearOperator<Real> {
85  private:
86  const ROL::Ptr<Objective<Real> > obj_;
87  const ROL::Ptr<Secant<Real> > secant_;
88  const ROL::Ptr<BoundConstraint<Real> > bnd_;
89  const ROL::Ptr<Vector<Real> > x_;
90  const ROL::Ptr<Vector<Real> > g_;
91  ROL::Ptr<Vector<Real> > v_;
92  Real eps_;
93  const bool useSecant_;
94  public:
95  PrecondPNK(const ROL::Ptr<Objective<Real> > &obj,
96  const ROL::Ptr<BoundConstraint<Real> > &bnd,
97  const ROL::Ptr<Vector<Real> > &x,
98  const ROL::Ptr<Vector<Real> > &g,
99  Real eps = 0 )
100  : obj_(obj), bnd_(bnd), x_(x), g_(g), eps_(eps), useSecant_(false) {
101  v_ = x_->clone();
102  }
103  PrecondPNK(const ROL::Ptr<Secant<Real> > &secant,
104  const ROL::Ptr<BoundConstraint<Real> > &bnd,
105  const ROL::Ptr<Vector<Real> > &x,
106  const ROL::Ptr<Vector<Real> > &g,
107  Real eps = 0 )
108  : secant_(secant), bnd_(bnd), x_(x), g_(g), eps_(eps), useSecant_(true) {
109  v_ = x_->clone();
110  }
111  void apply(Vector<Real> &Hv, const Vector<Real> &v, Real &tol) const {
112  Hv.set(v.dual());
113  }
114  void applyInverse(Vector<Real> &Hv, const Vector<Real> &v, Real &tol) const {
115  v_->set(v);
116  bnd_->pruneActive(*v_,*g_,*x_,eps_);
117  if ( useSecant_ ) {
118  secant_->applyH(Hv,*v_);
119  }
120  else {
121  obj_->precond(Hv,*v_,*x_,tol);
122  }
123  bnd_->pruneActive(Hv,*g_,*x_,eps_);
124  v_->set(v);
125  bnd_->pruneInactive(*v_,*g_,*x_,eps_);
126  Hv.plus(v_->dual());
127  }
128  };
129 
130 public:
131 
133  using Step<Real>::compute;
134  using Step<Real>::update;
135 
143  ProjectedNewtonKrylovStep( ROL::ParameterList &parlist, const bool computeObj = true )
144  : Step<Real>(), secant_(ROL::nullPtr), krylov_(ROL::nullPtr),
145  gp_(ROL::nullPtr), d_(ROL::nullPtr),
147  computeObj_(computeObj), useSecantPrecond_(false) {
148  // Parse ParameterList
149  ROL::ParameterList& Glist = parlist.sublist("General");
150  useSecantPrecond_ = Glist.sublist("Secant").get("Use as Preconditioner", false);
151  useProjectedGrad_ = Glist.get("Projected Gradient Criticality Measure", false);
152  verbosity_ = Glist.get("Print Verbosity",0);
153  // Initialize Krylov object
154  krylovName_ = Glist.sublist("Krylov").get("Type","Conjugate Gradients");
156  krylov_ = KrylovFactory<Real>(parlist);
157  // Initialize secant object
158  secantName_ = Glist.sublist("Secant").get("Type","Limited-Memory BFGS");
159  esec_ = StringToESecant(secantName_);
160  if ( useSecantPrecond_ ) {
161  secant_ = SecantFactory<Real>(parlist);
162  }
163  }
164 
175  ProjectedNewtonKrylovStep(ROL::ParameterList &parlist,
176  const ROL::Ptr<Krylov<Real> > &krylov,
177  const ROL::Ptr<Secant<Real> > &secant,
178  const bool computeObj = true)
179  : Step<Real>(), secant_(secant), krylov_(krylov),
181  gp_(ROL::nullPtr), d_(ROL::nullPtr),
183  computeObj_(computeObj), useSecantPrecond_(false) {
184  // Parse ParameterList
185  ROL::ParameterList& Glist = parlist.sublist("General");
186  useSecantPrecond_ = Glist.sublist("Secant").get("Use as Preconditioner", false);
187  useProjectedGrad_ = Glist.get("Projected Gradient Criticality Measure", false);
188  verbosity_ = Glist.get("Print Verbosity",0);
189  // Initialize secant object
190  if ( useSecantPrecond_ ) {
191  if (secant_ == ROL::nullPtr ) {
192  secantName_ = Glist.sublist("Secant").get("Type","Limited-Memory BFGS");
194  secant_ = SecantFactory<Real>(parlist);
195  }
196  else {
197  secantName_ = Glist.sublist("Secant").get("User Defined Secant Name",
198  "Unspecified User Defined Secant Method");
199  }
200  }
201  // Initialize Krylov object
202  if ( krylov_ == ROL::nullPtr ) {
203  krylovName_ = Glist.sublist("Krylov").get("Type","Conjugate Gradients");
205  krylov_ = KrylovFactory<Real>(parlist);
206  }
207  }
208 
209  void initialize( Vector<Real> &x, const Vector<Real> &s, const Vector<Real> &g,
211  AlgorithmState<Real> &algo_state ) {
212  Step<Real>::initialize(x,s,g,obj,bnd,algo_state);
213  gp_ = g.clone();
214  d_ = s.clone();
215  }
216 
217  void compute( Vector<Real> &s, const Vector<Real> &x,
219  AlgorithmState<Real> &algo_state ) {
220  Real one(1);
221  ROL::Ptr<StepState<Real> > step_state = Step<Real>::getState();
222 
223  // Build Hessian and Preconditioner object
224  ROL::Ptr<Objective<Real> > obj_ptr = ROL::makePtrFromRef(obj);
225  ROL::Ptr<BoundConstraint<Real> > bnd_ptr = ROL::makePtrFromRef(bnd);
226  ROL::Ptr<LinearOperator<Real> > hessian
227  = ROL::makePtr<HessianPNK>(obj_ptr,bnd_ptr,algo_state.iterateVec,
228  step_state->gradientVec,algo_state.gnorm);
229  ROL::Ptr<LinearOperator<Real> > precond;
230  if (useSecantPrecond_) {
231  precond = ROL::makePtr<PrecondPNK>(secant_,bnd_ptr,
232  algo_state.iterateVec,step_state->gradientVec,algo_state.gnorm);
233  }
234  else {
235  precond = ROL::makePtr<PrecondPNK>(obj_ptr,bnd_ptr,
236  algo_state.iterateVec,step_state->gradientVec,algo_state.gnorm);
237  }
238 
239  // Run Krylov method
240  flagKrylov_ = 0;
241  krylov_->run(s,*hessian,*(step_state->gradientVec),*precond,iterKrylov_,flagKrylov_);
242 
243  // Check Krylov flags
244  if ( flagKrylov_ == 2 && iterKrylov_ <= 1 ) {
245  s.set((step_state->gradientVec)->dual());
246  }
247  s.scale(-one);
248  }
249 
250  void update( Vector<Real> &x, const Vector<Real> &s,
252  AlgorithmState<Real> &algo_state ) {
253  Real tol = std::sqrt(ROL_EPSILON<Real>()), one(1);
254  ROL::Ptr<StepState<Real> > step_state = Step<Real>::getState();
255  step_state->SPiter = iterKrylov_;
256  step_state->SPflag = flagKrylov_;
257 
258  // Update iterate and store previous step
259  algo_state.iter++;
260  d_->set(x);
261  x.plus(s);
262  bnd.project(x);
263  (step_state->descentVec)->set(x);
264  (step_state->descentVec)->axpy(-one,*d_);
265  algo_state.snorm = s.norm();
266 
267  // Compute new gradient
268  if ( useSecantPrecond_ ) {
269  gp_->set(*(step_state->gradientVec));
270  }
271  obj.update(x,true,algo_state.iter);
272  if ( computeObj_ ) {
273  algo_state.value = obj.value(x,tol);
274  algo_state.nfval++;
275  }
276  obj.gradient(*(step_state->gradientVec),x,tol);
277  algo_state.ngrad++;
278 
279  // Update Secant Information
280  if ( useSecantPrecond_ ) {
281  secant_->updateStorage(x,*(step_state->gradientVec),*gp_,s,algo_state.snorm,algo_state.iter+1);
282  }
283 
284  // Update algorithm state
285  (algo_state.iterateVec)->set(x);
286  if ( useProjectedGrad_ ) {
287  gp_->set(*(step_state->gradientVec));
288  bnd.computeProjectedGradient( *gp_, x );
289  algo_state.gnorm = gp_->norm();
290  }
291  else {
292  d_->set(x);
293  d_->axpy(-one,(step_state->gradientVec)->dual());
294  bnd.project(*d_);
295  d_->axpy(-one,x);
296  algo_state.gnorm = d_->norm();
297  }
298  }
299 
300  std::string printHeader( void ) const {
301  std::stringstream hist;
302 
303  if( verbosity_>0 ) {
304  hist << std::string(109,'-') << "\n";
306  hist << " status output definitions\n\n";
307  hist << " iter - Number of iterates (steps taken) \n";
308  hist << " value - Objective function value \n";
309  hist << " gnorm - Norm of the gradient\n";
310  hist << " snorm - Norm of the step (update to optimization vector)\n";
311  hist << " #fval - Cumulative number of times the objective function was evaluated\n";
312  hist << " #grad - Number of times the gradient was computed\n";
313  hist << " iterCG - Number of Krylov iterations used to compute search direction\n";
314  hist << " flagCG - Krylov solver flag" << "\n";
315  hist << std::string(109,'-') << "\n";
316  }
317 
318  hist << " ";
319  hist << std::setw(6) << std::left << "iter";
320  hist << std::setw(15) << std::left << "value";
321  hist << std::setw(15) << std::left << "gnorm";
322  hist << std::setw(15) << std::left << "snorm";
323  hist << std::setw(10) << std::left << "#fval";
324  hist << std::setw(10) << std::left << "#grad";
325  hist << std::setw(10) << std::left << "iterCG";
326  hist << std::setw(10) << std::left << "flagCG";
327  hist << "\n";
328  return hist.str();
329  }
330  std::string printName( void ) const {
331  std::stringstream hist;
332  hist << "\n" << EDescentToString(DESCENT_NEWTONKRYLOV);
333  hist << " using " << krylovName_;
334  if ( useSecantPrecond_ ) {
335  hist << " with " << secantName_ << " preconditioning";
336  }
337  hist << "\n";
338  return hist.str();
339  }
340  std::string print( AlgorithmState<Real> &algo_state, bool print_header = false ) const {
341  std::stringstream hist;
342  hist << std::scientific << std::setprecision(6);
343  if ( algo_state.iter == 0 ) {
344  hist << printName();
345  }
346  if ( print_header ) {
347  hist << printHeader();
348  }
349  if ( algo_state.iter == 0 ) {
350  hist << " ";
351  hist << std::setw(6) << std::left << algo_state.iter;
352  hist << std::setw(15) << std::left << algo_state.value;
353  hist << std::setw(15) << std::left << algo_state.gnorm;
354  hist << "\n";
355  }
356  else {
357  hist << " ";
358  hist << std::setw(6) << std::left << algo_state.iter;
359  hist << std::setw(15) << std::left << algo_state.value;
360  hist << std::setw(15) << std::left << algo_state.gnorm;
361  hist << std::setw(15) << std::left << algo_state.snorm;
362  hist << std::setw(10) << std::left << algo_state.nfval;
363  hist << std::setw(10) << std::left << algo_state.ngrad;
364  hist << std::setw(10) << std::left << iterKrylov_;
365  hist << std::setw(10) << std::left << flagKrylov_;
366  hist << "\n";
367  }
368  return hist.str();
369  }
370 }; // class ProjectedNewtonKrylovStep
371 
372 } // namespace ROL
373 
374 #endif
Provides the interface to evaluate objective functions.
void applyInverse(Vector< Real > &Hv, const Vector< Real > &v, Real &tol) const
Apply inverse of linear operator.
virtual const Vector & dual() const
Return dual representation of , for example, the result of applying a Riesz map, or change of basis...
Definition: ROL_Vector.hpp:192
bool useSecantPrecond_
Whether or not a secant approximation is used for preconditioning inexact Newton. ...
ROL::Ptr< Secant< Real > > secant_
Secant object (used for quasi-Newton)
virtual void scale(const Real alpha)=0
Compute where .
virtual ROL::Ptr< Vector > clone() const =0
Clone to make a new (uninitialized) vector.
void update(Vector< Real > &x, const Vector< Real > &s, Objective< Real > &obj, BoundConstraint< Real > &bnd, AlgorithmState< Real > &algo_state)
Update step, if successful.
virtual void plus(const Vector &x)=0
Compute , where .
const ROL::Ptr< BoundConstraint< Real > > bnd_
void apply(Vector< Real > &Hv, const Vector< Real > &v, Real &tol) const
Apply linear operator.
virtual Real value(const Vector< Real > &x, Real &tol)=0
Compute value.
Provides the interface to compute optimization steps.
Definition: ROL_Step.hpp:34
Contains definitions of custom data types in ROL.
void compute(Vector< Real > &s, const Vector< Real > &x, Objective< Real > &obj, BoundConstraint< Real > &bnd, AlgorithmState< Real > &algo_state)
Compute step.
void apply(Vector< Real > &Hv, const Vector< Real > &v, Real &tol) const
Apply linear operator.
ESecant StringToESecant(std::string s)
Definition: ROL_Types.hpp:509
std::string EDescentToString(EDescent tr)
Definition: ROL_Types.hpp:386
Defines the linear algebra or vector space interface.
Definition: ROL_Vector.hpp:46
Provides the interface to compute optimization steps with projected inexact ProjectedNewton&#39;s method ...
virtual void update(const Vector< Real > &x, UpdateType type, int iter=-1)
Update objective function.
ProjectedNewtonKrylovStep(ROL::ParameterList &parlist, const bool computeObj=true)
Constructor.
EKrylov
Enumeration of Krylov methods.
std::string printName(void) const
Print step name.
EKrylov StringToEKrylov(std::string s)
PrecondPNK(const ROL::Ptr< Objective< Real > > &obj, const ROL::Ptr< BoundConstraint< Real > > &bnd, const ROL::Ptr< Vector< Real > > &x, const ROL::Ptr< Vector< Real > > &g, Real eps=0)
ProjectedNewtonKrylovStep(ROL::ParameterList &parlist, const ROL::Ptr< Krylov< Real > > &krylov, const ROL::Ptr< Secant< Real > > &secant, const bool computeObj=true)
Constructor.
State for algorithm class. Will be used for restarts.
Definition: ROL_Types.hpp:109
PrecondPNK(const ROL::Ptr< Secant< Real > > &secant, const ROL::Ptr< BoundConstraint< Real > > &bnd, const ROL::Ptr< Vector< Real > > &x, const ROL::Ptr< Vector< Real > > &g, Real eps=0)
std::string printHeader(void) const
Print iterate header.
virtual void gradient(Vector< Real > &g, const Vector< Real > &x, Real &tol)
Compute gradient.
bool useProjectedGrad_
Whether or not to use to the projected gradient criticality measure.
ESecant
Enumeration of secant update algorithms.
Definition: ROL_Types.hpp:452
ROL::Ptr< StepState< Real > > getState(void)
Definition: ROL_Step.hpp:39
void initialize(Vector< Real > &x, const Vector< Real > &s, const Vector< Real > &g, Objective< Real > &obj, BoundConstraint< Real > &bnd, AlgorithmState< Real > &algo_state)
Initialize step with bound constraint.
int flagKrylov_
Termination flag for Krylov method (used for inexact Newton)
Provides interface for and implements limited-memory secant operators.
Definition: ROL_Secant.hpp:45
ROL::Ptr< Vector< Real > > iterateVec
Definition: ROL_Types.hpp:123
virtual void project(Vector< Real > &x)
Project optimization variables onto the bounds.
Provides definitions for Krylov solvers.
Definition: ROL_Krylov.hpp:24
Provides the interface to apply a linear operator.
Provides the interface to apply upper and lower bound constraints.
HessianPNK(const ROL::Ptr< Objective< Real > > &obj, const ROL::Ptr< BoundConstraint< Real > > &bnd, const ROL::Ptr< Vector< Real > > &x, const ROL::Ptr< Vector< Real > > &g, Real eps=0)
void computeProjectedGradient(Vector< Real > &g, const Vector< Real > &x)
Compute projected gradient.
int iterKrylov_
Number of Krylov iterations (used for inexact Newton)
virtual void initialize(Vector< Real > &x, const Vector< Real > &g, Objective< Real > &obj, BoundConstraint< Real > &con, AlgorithmState< Real > &algo_state)
Initialize step with bound constraint.
Definition: ROL_Step.hpp:54
virtual void set(const Vector &x)
Set where .
Definition: ROL_Vector.hpp:175
const ROL::Ptr< BoundConstraint< Real > > bnd_
virtual Real norm() const =0
Returns where .
std::string print(AlgorithmState< Real > &algo_state, bool print_header=false) const
Print iterate status.
ROL::Ptr< Krylov< Real > > krylov_
Krylov solver object (used for inexact Newton)