decl/structured-panoc-lbfgs.hpp File Reference

#include <alpaqa/inner/decl/lbfgs-stepsize.hpp>
#include <alpaqa/inner/decl/panoc-fwd.hpp>
#include <alpaqa/inner/decl/panoc-stop-crit.hpp>
#include <alpaqa/inner/directions/decl/lbfgs.hpp>
#include <alpaqa/util/atomic_stop_signal.hpp>
#include <alpaqa/util/lipschitz.hpp>
#include <alpaqa/util/problem.hpp>
#include <alpaqa/util/solverstatus.hpp>
#include <atomic>
#include <chrono>
#include <limits>
#include <string>

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Classes
struct	StructuredPANOCLBFGSParams
	Tuning parameters for the second order PANOC algorithm. More...
struct	StructuredPANOCLBFGSProgressInfo
struct	StructuredPANOCLBFGSStats
class	StructuredPANOCLBFGSSolver
	Second order PANOC solver for ALM. More...
struct	InnerStatsAccumulator< StructuredPANOCLBFGSStats >

Namespaces
namespace	alpaqa

Functions
InnerStatsAccumulator< StructuredPANOCLBFGSStats > &	operator+= (InnerStatsAccumulator< StructuredPANOCLBFGSStats > &acc, const StructuredPANOCLBFGSStats &s)

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Class Documentation

alpaqa::StructuredPANOCLBFGSParams

struct alpaqa::StructuredPANOCLBFGSParams

Collaboration diagram for StructuredPANOCLBFGSParams:

Class Members
LipschitzEstimateParams	Lipschitz	Parameters related to the Lipschitz constant estimate and step size.
unsigned	max_iter	Maximum number of inner PANOC iterations.
microseconds	max_time	Maximum duration.
real_t	τ_min	Minimum weight factor between Newton step and projected gradient step.
real_t	L_min	Minimum Lipschitz constant estimate.
real_t	L_max	Maximum Lipschitz constant estimate.
real_t	nonmonotone_linesearch	Factor used in update for exponentially weighted nonmonotone line search. Zero means monotone line search.
PANOCStopCrit	stop_crit	What stopping criterion to use.
unsigned	max_no_progress	Maximum number of iterations without any progress before giving up.
unsigned	print_interval	When to print progress. If set to zero, nothing will be printed. If set to N != 0, progress is printed every N iterations.
real_t	quadratic_upperbound_tolerance_factor
bool	update_lipschitz_in_linesearch
bool	alternative_linesearch_cond
bool	hessian_vec
bool	hessian_vec_finite_differences
bool	full_augmented_hessian
unsigned	hessian_step_size_heuristic
LBFGSStepSize	lbfgs_stepsize

alpaqa::StructuredPANOCLBFGSProgressInfo

struct alpaqa::StructuredPANOCLBFGSProgressInfo

Collaboration diagram for StructuredPANOCLBFGSProgressInfo:

Class Members
unsigned	k
crvec	x
crvec	p
real_t	norm_sq_p
crvec	x_hat
real_t	φγ
real_t	ψ
crvec	grad_ψ
real_t	ψ_hat
crvec	grad_ψ_hat
real_t	L
real_t	γ
real_t	τ
real_t	ε
crvec	Σ
crvec	y
const Problem &	problem
const StructuredPANOCLBFGSParams &	params

alpaqa::StructuredPANOCLBFGSStats

struct alpaqa::StructuredPANOCLBFGSStats

Collaboration diagram for StructuredPANOCLBFGSStats:

Class Members
SolverStatus	status
real_t	ε
microseconds	elapsed_time
unsigned	iterations
unsigned	linesearch_failures
unsigned	lbfgs_failures
unsigned	lbfgs_rejected
unsigned	τ_1_accepted
unsigned	count_τ
real_t	sum_τ

alpaqa::InnerStatsAccumulator< StructuredPANOCLBFGSStats >

struct alpaqa::InnerStatsAccumulator< StructuredPANOCLBFGSStats >

Collaboration diagram for InnerStatsAccumulator< StructuredPANOCLBFGSStats >:

Class Members
microseconds	elapsed_time	Total elapsed time in the inner solver.
unsigned	iterations	Total number of inner PANOC iterations.
unsigned	linesearch_failures	Total number of PANOC line search failures.
unsigned	lbfgs_failures	Total number of times that the L-BFGS direction was not finite.
unsigned	lbfgs_rejected	Total number of times that the L-BFGS update was rejected (i.e. it could have resulted in a non-positive definite Hessian estimate).
unsigned	τ_1_accepted	Total number of times that a line search parameter of \( \tau = 1 \) was accepted (i.e. no backtracking necessary).
unsigned	count_τ	The total number of line searches performed (used for computing the average value of \( \tau \)).
real_t	sum_τ	The sum of the line search parameter \( \tau \) in all iterations (used for computing the average value of \( \tau \)).