%%% -*- Mode: Prolog; -*- % This file is part of YAP-LBFGS. % Copyright (C) 2009 Bernd Gutmann % % YAP-LBFGS is free software: you can redistribute it and/or modify % it under the terms of the GNU General Public License as published by % the Free Software Foundation, either version 3 of the License, or % (at your option) any later version. % % YAP-LBFGS is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with YAP-LBFGS. If not, see . :- module(lbfgs,[optimizer_initialize/3, optimizer_initialize/4, optimizer_run/2, optimizer_get_x/2, optimizer_set_x/2, optimizer_get_g/2, optimizer_set_g/2, optimizer_finalize/0, optimizer_set_parameter/2, optimizer_get_parameter/2, optimizer_parameters/0]). % switch on all the checks to reduce bug searching time % :- yap_flag(unknown,error). % :- style_check(single_var). :- dynamic initialized/0. :- load_foreign_files(['yap_lbfgs'],[],'init_lbfgs_predicates'). optimizer_initialize(N,Call_Evaluate,Call_Progress) :- optimizer_initialize(N,user,Call_Evaluate,Call_Progress). optimizer_initialize(N,Module,Call_Evaluate,Call_Progress) :- \+ initialized, integer(N), N>0, % check whether there are such call back functions current_module(Module), current_predicate(Module:Call_Evaluate/3), current_predicate(Module:Call_Progress/8), optimizer_reserve_memory(N), % install call back predicates in the user module which call % the predicates given by the arguments EvalGoal =.. [Call_Evaluate,E1,E2,E3], ProgressGoal =.. [Call_Progress,P1,P2,P3,P4,P5,P6,P7,P8], retractall( user:'$lbfgs_callback_evaluate'(_E1,_E2,_E3) ), retractall( user:'$lbfgs_callback_progress'(_P1,_P2,_P3,_P4,_P5,_P6,_P7,_P8) ), assert( (user:'$lbfgs_callback_evaluate'(E1,E2,E3) :- Module:EvalGoal, !) ), assert( (user:'$lbfgs_callback_progress'(P1,P2,P3,P4,P5,P6,P7,P8) :- Module:ProgressGoal, !) ), assert(initialized). optimizer_finalize :- initialized, optimizer_free_memory, retractall(user:'$lbfgs_callback_evaluate'(_,_,_)), retractall(user:'$lbfgs_callback_progress'(_,_,_,_,_,_,_,_)), retractall(initialized). optimizer_parameters :- optimizer_get_parameter(m,M), optimizer_get_parameter(epsilon,Epsilon), optimizer_get_parameter(past,Past), optimizer_get_parameter(delta,Delta), optimizer_get_parameter(max_iterations,Max_Iterations), optimizer_get_parameter(linesearch,Linesearch), optimizer_get_parameter(max_linesearch,Max_Linesearch), optimizer_get_parameter(min_step,Min_Step), optimizer_get_parameter(max_step,Max_Step), optimizer_get_parameter(ftol,Ftol), optimizer_get_parameter(gtol,Gtol), optimizer_get_parameter(xtol,Xtol), optimizer_get_parameter(orthantwise_c,Orthantwise_C), optimizer_get_parameter(orthantwise_start,Orthantwise_Start), optimizer_get_parameter(orthantwise_end,Orthantwise_End), format('/******************************************************************************************~n',[]), print_param('Name','Value','Description','Type'), format('******************************************************************************************~n',[]), print_param(m,M,'The number of corrections to approximate the inverse hessian matrix.',int), print_param(epsilon,Epsilon,'Epsilon for convergence test.',float), print_param(past,Past,'Distance for delta-based convergence test.',int), print_param(delta,Delta,'Delta for convergence test.',float), print_param(max_iterations,Max_Iterations,'The maximum number of iterations',int), print_param(linesearch,Linesearch,'The line search algorithm.',int), print_param(max_linesearch,Max_Linesearch,'The maximum number of trials for the line search.',int), print_param(min_step,Min_Step,'The minimum step of the line search routine.',float), print_param(max_step,Max_Step,'The maximum step of the line search.',float), print_param(ftol,Ftol,'A parameter to control the accuracy of the line search routine.',float), print_param(gtol,Gtol,'A parameter to control the accuracy of the line search routine.',float), print_param(xtol,Xtol,'The machine precision for floating-point values.',float), print_param(orthantwise_c,Orthantwise_C,'Coefficient for the L1 norm of variables',float), print_param(orthantwise_start,Orthantwise_Start,'Start index for computing the L1 norm of the variables.',int), print_param(orthantwise_end,Orthantwise_End,'End index for computing the L1 norm of the variables.',int), format('******************************************************************************************/~n',[]), format(' use optimizer_set_paramater(Name,Value) to change parameters~n',[]), format(' use optimizer_get_parameter(Name,Value) to see current parameters~n',[]), format(' use optimizer_parameters to print this overview~2n',[]). print_param(Name,Value,Text,Dom) :- format(user,'~w~10+~w~19+~w~15+~w~30+~n',[Dom,Name,Value,Text]).