PETSC_EXTERN void PETSC_STDCALL taosethessianroutine_(Tao *tao, Mat *J, Mat *Jp, void (PETSC_STDCALL *func)(Tao*, Vec *, Mat *, Mat *,void *, PetscErrorCode *), void *ctx, PetscErrorCode *ierr)
{
PetscObjectAllocateFortranPointers(*tao,NFUNCS);
if (!func) {
*ierr = TaoSetHessianRoutine(*tao,*J,*Jp,0,ctx);
} else {
((PetscObject)*tao)->fortran_func_pointers[HESS] = (PetscVoidFunction)func;
*ierr = TaoSetHessianRoutine(*tao,*J, *Jp, ourtaohessianroutine,ctx);
}
}
int main(int argc,char **argv)
{
PetscErrorCode ierr; /* used to check for functions returning nonzeros */
PetscReal zero=0.0;
Vec x; /* solution vector */
Mat H;
Tao tao; /* Tao solver context */
PetscBool flg;
PetscMPIInt size,rank; /* number of processes running */
AppCtx user; /* user-defined application context */
/* Initialize TAO and PETSc */
PetscInitialize(&argc,&argv,(char*)0,help);
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr);
if (size >1) SETERRQ(PETSC_COMM_SELF,1,"Incorrect number of processors");
/* Initialize problem parameters */
user.n = 2; user.alpha = 99.0;
/* Check for command line arguments to override defaults */
ierr = PetscOptionsGetInt(NULL,NULL,"-n",&user.n,&flg);CHKERRQ(ierr);
ierr = PetscOptionsGetReal(NULL,NULL,"-alpha",&user.alpha,&flg);CHKERRQ(ierr);
/* Allocate vectors for the solution and gradient */
ierr = VecCreateSeq(PETSC_COMM_SELF,user.n,&x);CHKERRQ(ierr);
ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,2,user.n,user.n,1,NULL,&H);CHKERRQ(ierr);
/* The TAO code begins here */
/* Create TAO solver with desired solution method */
ierr = TaoCreate(PETSC_COMM_SELF,&tao);CHKERRQ(ierr);
ierr = TaoSetType(tao,TAOLMVM);CHKERRQ(ierr);
/* Set solution vec and an initial guess */
ierr = VecSet(x, zero);CHKERRQ(ierr);
ierr = TaoSetInitialVector(tao,x);CHKERRQ(ierr);
/* Set routines for function, gradient, hessian evaluation */
ierr = TaoSetObjectiveAndGradientRoutine(tao,FormFunctionGradient,&user);CHKERRQ(ierr);
ierr = TaoSetHessianRoutine(tao,H,H,FormHessian,&user);CHKERRQ(ierr);
/* Check for TAO command line options */
ierr = TaoSetFromOptions(tao);CHKERRQ(ierr);
/* SOLVE THE APPLICATION */
ierr = TaoSolve(tao);CHKERRQ(ierr);
ierr = TaoDestroy(&tao);CHKERRQ(ierr);
ierr = VecDestroy(&x);CHKERRQ(ierr);
ierr = MatDestroy(&H);CHKERRQ(ierr);
PetscFinalize();
return 0;
}
int main(int argc,char **argv)
{
PetscErrorCode ierr; /* used to check for functions returning nonzeros */
Vec x; /* solution vector */
Mat H; /* Hessian matrix */
Tao tao; /* Tao context */
AppCtx user; /* user-defined application context */
ierr = PetscInitialize(&argc,&argv,(char*)0,0);if (ierr) return ierr;
/* Initialize problem parameters */
user.n = 2; user.alpha = 99.0;
/* Allocate vectors for the solution and gradient */
ierr = VecCreateSeq(PETSC_COMM_SELF,user.n,&x); CHKERRQ(ierr);
ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,2,user.n,user.n,1,NULL,&H);
/* Create TAO solver with desired solution method */
ierr = TaoCreate(PETSC_COMM_SELF,&tao); CHKERRQ(ierr);
ierr = TaoSetType(tao,TAOLMVM); CHKERRQ(ierr);
/* Set solution vec and an initial guess */
ierr = VecSet(x, 0); CHKERRQ(ierr);
ierr = TaoSetInitialVector(tao,x); CHKERRQ(ierr);
/* Set routines for function, gradient, hessian evaluation */
ierr = TaoSetObjectiveAndGradientRoutine(tao,FormFunctionGradient,&user);
ierr = TaoSetHessianRoutine(tao,H,H,FormHessian,&user); CHKERRQ(ierr);
/* Check for TAO command line options */
ierr = TaoSetFromOptions(tao); CHKERRQ(ierr);
/* Solve the application */
ierr = TaoSolve(tao); CHKERRQ(ierr);
/* Free data structures */
ierr = TaoDestroy(&tao); CHKERRQ(ierr);
ierr = VecDestroy(&x); CHKERRQ(ierr);
ierr = MatDestroy(&H); CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}
int main(int argc,char **argv)
{
PetscErrorCode ierr; /* used to check for functions returning nonzeros */
PetscReal zero=0.0;
Vec x; /* solution vector */
Mat H;
Tao tao; /* Tao solver context */
PetscBool flg, test_lmvm = PETSC_FALSE;
PetscMPIInt size,rank; /* number of processes running */
AppCtx user; /* user-defined application context */
TaoConvergedReason reason;
PetscInt its, recycled_its=0, oneshot_its=0;
/* Initialize TAO and PETSc */
ierr = PetscInitialize(&argc,&argv,(char*)0,help);if (ierr) return ierr;
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr);
if (size >1) SETERRQ(PETSC_COMM_SELF,1,"Incorrect number of processors");
/* Initialize problem parameters */
user.n = 2; user.alpha = 99.0; user.chained = PETSC_FALSE;
/* Check for command line arguments to override defaults */
ierr = PetscOptionsGetInt(NULL,NULL,"-n",&user.n,&flg);CHKERRQ(ierr);
ierr = PetscOptionsGetReal(NULL,NULL,"-alpha",&user.alpha,&flg);CHKERRQ(ierr);
ierr = PetscOptionsGetBool(NULL,NULL,"-chained",&user.chained,&flg);CHKERRQ(ierr);
ierr = PetscOptionsGetBool(NULL,NULL,"-test_lmvm",&test_lmvm,&flg);CHKERRQ(ierr);
/* Allocate vectors for the solution and gradient */
ierr = VecCreateSeq(PETSC_COMM_SELF,user.n,&x);CHKERRQ(ierr);
ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,2,user.n,user.n,1,NULL,&H);CHKERRQ(ierr);
/* The TAO code begins here */
/* Create TAO solver with desired solution method */
ierr = TaoCreate(PETSC_COMM_SELF,&tao);CHKERRQ(ierr);
ierr = TaoSetType(tao,TAOLMVM);CHKERRQ(ierr);
/* Set solution vec and an initial guess */
ierr = VecSet(x, zero);CHKERRQ(ierr);
ierr = TaoSetInitialVector(tao,x);CHKERRQ(ierr);
/* Set routines for function, gradient, hessian evaluation */
ierr = TaoSetObjectiveAndGradientRoutine(tao,FormFunctionGradient,&user);CHKERRQ(ierr);
ierr = TaoSetHessianRoutine(tao,H,H,FormHessian,&user);CHKERRQ(ierr);
/* Check for TAO command line options */
ierr = TaoSetFromOptions(tao);CHKERRQ(ierr);
/* Solve the problem */
ierr = TaoSetTolerances(tao, 1.e-5, 0.0, 0.0);CHKERRQ(ierr);
ierr = TaoSetMaximumIterations(tao, 5);CHKERRQ(ierr);
ierr = TaoLMVMRecycle(tao, PETSC_TRUE);CHKERRQ(ierr);
reason = TAO_CONTINUE_ITERATING;
while (reason != TAO_CONVERGED_GATOL) {
ierr = TaoSolve(tao);CHKERRQ(ierr);
ierr = TaoGetConvergedReason(tao, &reason);CHKERRQ(ierr);
ierr = TaoGetIterationNumber(tao, &its);CHKERRQ(ierr);
recycled_its += its;
ierr = PetscPrintf(PETSC_COMM_SELF, "-----------------------\n");CHKERRQ(ierr);
}
/* Disable recycling and solve again! */
ierr = TaoSetMaximumIterations(tao, 100);CHKERRQ(ierr);
ierr = TaoLMVMRecycle(tao, PETSC_FALSE);CHKERRQ(ierr);
ierr = VecSet(x, zero);CHKERRQ(ierr);
ierr = TaoSolve(tao);CHKERRQ(ierr);
ierr = TaoGetConvergedReason(tao, &reason);CHKERRQ(ierr);
if (reason != TAO_CONVERGED_GATOL) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_NOT_CONVERGED, "Solution failed to converge!");
ierr = TaoGetIterationNumber(tao, &oneshot_its);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_SELF, "-----------------------\n");CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_SELF, "recycled its: %D | oneshot its: %D\n", recycled_its, oneshot_its);CHKERRQ(ierr);
if (recycled_its != oneshot_its) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_NOT_CONVERGED, "LMVM recycling does not work!");
ierr = TaoDestroy(&tao);CHKERRQ(ierr);
ierr = VecDestroy(&x);CHKERRQ(ierr);
ierr = MatDestroy(&H);CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}
PetscErrorCode main(int argc,char **argv)
{
PetscErrorCode ierr; /* used to check for functions returning nonzeros */
PetscMPIInt size;
Vec x; /* solution */
KSP ksp;
PC pc;
Vec ceq,cin;
PetscBool flg; /* A return value when checking for use options */
Tao tao; /* Tao solver context */
TaoConvergedReason reason;
AppCtx user; /* application context */
/* Initialize TAO,PETSc */
ierr = PetscInitialize(&argc,&argv,(char *)0,help);CHKERRQ(ierr);
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
/* Specify default parameters for the problem, check for command-line overrides */
ierr = PetscStrncpy(user.name,"HS21",8);CHKERRQ(ierr);
ierr = PetscOptionsGetString(NULL,NULL,"-cutername",user.name,24,&flg);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD,"\n---- MAROS Problem %s -----\n",user.name);CHKERRQ(ierr);
ierr = InitializeProblem(&user);CHKERRQ(ierr);
ierr = VecDuplicate(user.d,&x);CHKERRQ(ierr);
ierr = VecDuplicate(user.beq,&ceq);CHKERRQ(ierr);
ierr = VecDuplicate(user.bin,&cin);CHKERRQ(ierr);
ierr = VecSet(x,1.0);CHKERRQ(ierr);
ierr = TaoCreate(PETSC_COMM_WORLD,&tao);CHKERRQ(ierr);
ierr = TaoSetType(tao,TAOIPM);CHKERRQ(ierr);
ierr = TaoSetInitialVector(tao,x);CHKERRQ(ierr);
ierr = TaoSetObjectiveAndGradientRoutine(tao,FormFunctionGradient,(void*)&user);CHKERRQ(ierr);
ierr = TaoSetEqualityConstraintsRoutine(tao,ceq,FormEqualityConstraints,(void*)&user);CHKERRQ(ierr);
ierr = TaoSetInequalityConstraintsRoutine(tao,cin,FormInequalityConstraints,(void*)&user);CHKERRQ(ierr);
ierr = TaoSetInequalityBounds(tao,user.bin,NULL);CHKERRQ(ierr);
ierr = TaoSetJacobianEqualityRoutine(tao,user.Aeq,user.Aeq,FormEqualityJacobian,(void*)&user);CHKERRQ(ierr);
ierr = TaoSetJacobianInequalityRoutine(tao,user.Ain,user.Ain,FormInequalityJacobian,(void*)&user);CHKERRQ(ierr);
ierr = TaoSetHessianRoutine(tao,user.H,user.H,FormHessian,(void*)&user);CHKERRQ(ierr);
ierr = TaoGetKSP(tao,&ksp);CHKERRQ(ierr);
ierr = KSPGetPC(ksp,&pc);CHKERRQ(ierr);
ierr = PCSetType(pc,PCLU);CHKERRQ(ierr);
/*
This algorithm produces matrices with zeros along the diagonal therefore we need to use
SuperLU which does partial pivoting
*/
ierr = PCFactorSetMatSolverPackage(pc,MATSOLVERSUPERLU);CHKERRQ(ierr);
ierr = KSPSetType(ksp,KSPPREONLY);CHKERRQ(ierr);
ierr = TaoSetTolerances(tao,0,0,0);CHKERRQ(ierr);
ierr = TaoSetFromOptions(tao);CHKERRQ(ierr);
ierr = TaoSolve(tao);CHKERRQ(ierr);
ierr = TaoGetConvergedReason(tao,&reason);CHKERRQ(ierr);
if (reason < 0) {
ierr = PetscPrintf(MPI_COMM_WORLD, "TAO failed to converge due to %s.\n",TaoConvergedReasons[reason]);CHKERRQ(ierr);
} else {
ierr = PetscPrintf(MPI_COMM_WORLD, "Optimization completed with status %s.\n",TaoConvergedReasons[reason]);CHKERRQ(ierr);
}
ierr = DestroyProblem(&user);CHKERRQ(ierr);
ierr = VecDestroy(&x);CHKERRQ(ierr);
ierr = VecDestroy(&ceq);CHKERRQ(ierr);
ierr = VecDestroy(&cin);CHKERRQ(ierr);
ierr = TaoDestroy(&tao);CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}
void TaoOptimizationSolver<T>::solve ()
{
LOG_SCOPE("solve()", "TaoOptimizationSolver");
this->init ();
this->system().solution->zero();
PetscMatrix<T> * hessian = cast_ptr<PetscMatrix<T> *>(this->system().matrix);
// PetscVector<T> * gradient = cast_ptr<PetscVector<T> *>(this->system().rhs);
PetscVector<T> * x = cast_ptr<PetscVector<T> *>(this->system().solution.get());
PetscVector<T> * ceq = cast_ptr<PetscVector<T> *>(this->system().C_eq.get());
PetscMatrix<T> * ceq_jac = cast_ptr<PetscMatrix<T> *>(this->system().C_eq_jac.get());
PetscVector<T> * cineq = cast_ptr<PetscVector<T> *>(this->system().C_ineq.get());
PetscMatrix<T> * cineq_jac = cast_ptr<PetscMatrix<T> *>(this->system().C_ineq_jac.get());
PetscVector<T> * lb = cast_ptr<PetscVector<T> *>(&this->system().get_vector("lower_bounds"));
PetscVector<T> * ub = cast_ptr<PetscVector<T> *>(&this->system().get_vector("upper_bounds"));
// Set the starting guess to zero.
x->zero();
PetscErrorCode ierr = 0;
// Workaround for bug where TaoSetFromOptions *reset*
// programmatically set tolerance and max. function evaluation
// values when "-tao_type ipm" was specified on the command line: we
// call TaoSetFromOptions twice (both before and after setting
// custom options programatically)
ierr = TaoSetFromOptions(_tao);
LIBMESH_CHKERR(ierr);
// Set convergence tolerances
// f(X) - f(X*) (estimated) <= fatol
// |f(X) - f(X*)| (estimated) / |f(X)| <= frtol
// ||g(X)|| <= gatol
// ||g(X)|| / |f(X)| <= grtol
// ||g(X)|| / ||g(X0)|| <= gttol
// Command line equivalents: -tao_fatol, -tao_frtol, -tao_gatol, -tao_grtol, -tao_gttol
ierr = TaoSetTolerances(_tao,
#if PETSC_RELEASE_LESS_THAN(3,7,0)
// Releases up to 3.X.Y had fatol and frtol, after that they were removed.
// Hopefully we'll be able to know X and Y soon. Guessing at 3.7.0.
/*fatol=*/PETSC_DEFAULT,
/*frtol=*/PETSC_DEFAULT,
#endif
/*gatol=*/PETSC_DEFAULT,
/*grtol=*/this->objective_function_relative_tolerance,
/*gttol=*/PETSC_DEFAULT);
LIBMESH_CHKERR(ierr);
// Set the max-allowed number of objective function evaluations
// Command line equivalent: -tao_max_funcs
ierr = TaoSetMaximumFunctionEvaluations(_tao, this->max_objective_function_evaluations);
LIBMESH_CHKERR(ierr);
// Set the max-allowed number of optimization iterations.
// Command line equivalent: -tao_max_it
// Not implemented for now as it seems fairly similar to
// ierr = TaoSetMaximumIterations(_tao, 4);
// LIBMESH_CHKERR(ierr);
// Set solution vec and an initial guess
ierr = TaoSetInitialVector(_tao, x->vec());
LIBMESH_CHKERR(ierr);
// We have to have an objective function
libmesh_assert( this->objective_object );
// Set routines for objective, gradient, hessian evaluation
ierr = TaoSetObjectiveRoutine(_tao, __libmesh_tao_objective, this);
LIBMESH_CHKERR(ierr);
if ( this->gradient_object )
{
ierr = TaoSetGradientRoutine(_tao, __libmesh_tao_gradient, this);
LIBMESH_CHKERR(ierr);
}
if ( this->hessian_object )
{
ierr = TaoSetHessianRoutine(_tao, hessian->mat(), hessian->mat(), __libmesh_tao_hessian, this);
LIBMESH_CHKERR(ierr);
}
if ( this->lower_and_upper_bounds_object )
{
// Need to actually compute the bounds vectors first
this->lower_and_upper_bounds_object->lower_and_upper_bounds(this->system());
ierr = TaoSetVariableBounds(_tao,
lb->vec(),
ub->vec());
LIBMESH_CHKERR(ierr);
}
if ( this->equality_constraints_object )
{
ierr = TaoSetEqualityConstraintsRoutine(_tao, ceq->vec(), __libmesh_tao_equality_constraints, this);
LIBMESH_CHKERR(ierr);
}
if ( this->equality_constraints_jacobian_object )
{
ierr = TaoSetJacobianEqualityRoutine(_tao,
ceq_jac->mat(),
ceq_jac->mat(),
__libmesh_tao_equality_constraints_jacobian,
this);
LIBMESH_CHKERR(ierr);
}
// Optionally set inequality constraints
if ( this->inequality_constraints_object )
{
ierr = TaoSetInequalityConstraintsRoutine(_tao, cineq->vec(), __libmesh_tao_inequality_constraints, this);
LIBMESH_CHKERR(ierr);
}
// Optionally set inequality constraints Jacobian
if ( this->inequality_constraints_jacobian_object )
{
ierr = TaoSetJacobianInequalityRoutine(_tao,
cineq_jac->mat(),
cineq_jac->mat(),
__libmesh_tao_inequality_constraints_jacobian,
this);
LIBMESH_CHKERR(ierr);
}
// Check for Tao command line options
ierr = TaoSetFromOptions(_tao);
LIBMESH_CHKERR(ierr);
// Perform the optimization
ierr = TaoSolve(_tao);
LIBMESH_CHKERR(ierr);
// Store the convergence/divergence reason
ierr = TaoGetConvergedReason(_tao, &_reason);
LIBMESH_CHKERR(ierr);
}
PetscErrorCode main(int argc,char **argv)
{
PetscErrorCode ierr; /* used to check for functions returning nonzeros */
Tao tao;
KSP ksp;
PC pc;
AppCtx user; /* application context */
ierr = PetscInitialize(&argc,&argv,(char *)0,help);
CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD,"\n---- TOY Problem -----\n");
CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD,"Solution should be f(1,1)=-2\n");
CHKERRQ(ierr);
ierr = InitializeProblem(&user);
CHKERRQ(ierr);
ierr = TaoCreate(PETSC_COMM_WORLD,&tao);
CHKERRQ(ierr);
ierr = TaoSetType(tao,TAOIPM);
CHKERRQ(ierr);
ierr = TaoSetInitialVector(tao,user.x);
CHKERRQ(ierr);
ierr = TaoSetVariableBounds(tao,user.xl,user.xu);
CHKERRQ(ierr);
ierr = TaoSetObjectiveAndGradientRoutine(tao,FormFunctionGradient,(void*)&user);
CHKERRQ(ierr);
ierr = TaoSetEqualityConstraintsRoutine(tao,user.ce,FormEqualityConstraints,(void*)&user);
CHKERRQ(ierr);
ierr = TaoSetInequalityConstraintsRoutine(tao,user.ci,FormInequalityConstraints,(void*)&user);
CHKERRQ(ierr);
ierr = TaoSetJacobianEqualityRoutine(tao,user.Ae,user.Ae,FormEqualityJacobian,(void*)&user);
CHKERRQ(ierr);
ierr = TaoSetJacobianInequalityRoutine(tao,user.Ai,user.Ai,FormInequalityJacobian,(void*)&user);
CHKERRQ(ierr);
ierr = TaoSetHessianRoutine(tao,user.H,user.H,FormHessian,(void*)&user);
CHKERRQ(ierr);
ierr = TaoSetTolerances(tao,0,0,0);
CHKERRQ(ierr);
ierr = TaoSetFromOptions(tao);
CHKERRQ(ierr);
ierr = TaoGetKSP(tao,&ksp);
CHKERRQ(ierr);
ierr = KSPGetPC(ksp,&pc);
CHKERRQ(ierr);
ierr = PCSetType(pc,PCLU);
CHKERRQ(ierr);
/*
This algorithm produces matrices with zeros along the diagonal therefore we need to use
SuperLU which does partial pivoting
*/
ierr = PCFactorSetMatSolverPackage(pc,MATSOLVERSUPERLU);
CHKERRQ(ierr);
ierr = KSPSetType(ksp,KSPPREONLY);
CHKERRQ(ierr);
ierr = KSPSetFromOptions(ksp);
CHKERRQ(ierr);
ierr = TaoSetTolerances(tao,0,0,0);
CHKERRQ(ierr);
ierr = TaoSolve(tao);
CHKERRQ(ierr);
ierr = DestroyProblem(&user);
CHKERRQ(ierr);
ierr = TaoDestroy(&tao);
CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}
