yap-6.3/packages/ProbLog/learning/flags_learning.yap

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%  $Date: 2009-07-31 14:57:09 +0200 (Fri, 31 Jul 2009) $
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%  ProbLog was developed at Katholieke Universiteit Leuven
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%  Angelika Kimmig, Vitor Santos Costa, Bernd Gutmann
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%  Main authors of this file:
%  Bernd Gutmann
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:- module(flags_learning, [set_learning_flag/2,
	learning_flag/2,
	learning_flags/0]).

:- style_check(all).
:- yap_flag(unknown,error).

:- use_module(logger).
:- use_module('../problog/flags').
:- use_module('../problog/print').

:- ensure_loaded(library(system)).

:- dynamic init_method/5.
:- dynamic rebuild_bdds/1.
:- dynamic reuse_initialized_bdds/1.
:- dynamic learning_rate/1.
:- dynamic probability_initializer/3.
:- dynamic check_duplicate_bdds/1.
:- dynamic output_directory/1.
:- dynamic query_directory/1.
:- dynamic log_frequency/1.
:- dynamic alpha/1.
:- dynamic sigmoid_slope/1.
:- dynamic line_search/1.
:- dynamic line_search_tolerance/1.
:- dynamic line_search_tau/1.
:- dynamic line_search_never_stop/1.
:- dynamic line_search_interval/2.
:- dynamic verbosity_level/1.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% global parameters that can be set using set_learning_flag/2
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

learning_flag(Flag,Option) :-
	get_learning_flag(Flag,Option).

get_learning_flag(init_method,(Query,Probability,BDDFile,ProbFile,Call)) :-
	init_method(Query,Probability,BDDFile,ProbFile,Call).

get_learning_flag(rebuild_bdds,Iteration) :-
	rebuild_bdds(Iteration).

get_learning_flag(reuse_initialized_bdds,Flag) :-
	reuse_initialized_bdds(Flag).

get_learning_flag(learning_rate,R) :-
	learning_rate(R).

get_learning_flag(probability_initializer,(FactID,Probability,Query)) :-
	probability_initializer(FactID,Probability,Query).

get_learning_flag(check_duplicate_bdds,Flag) :-
	check_duplicate_bdds(Flag).

get_learning_flag(output_directory,Directory) :-
	output_directory(Directory).

get_learning_flag(query_directory,Directory) :-
	query_directory(Directory).

get_learning_flag(log_frequency,Frequency) :-
	log_frequency(Frequency).

get_learning_flag(alpha,Alpha) :-
	alpha(Alpha).

get_learning_flag(sigmoid_slope,Slope) :-
	sigmoid_slope(Slope).

get_learning_flag(line_search,Flag) :-
	line_search(Flag).

get_learning_flag(line_search_tolerance,Tolerance) :-
	line_search_tolerance(Tolerance).

get_learning_flag(line_search_interval,(L,R)) :-
	line_search_interval(L,R).

get_learning_flag(line_search_tau,Tau) :-
	line_search_tau(Tau).

get_learning_flag(line_search_never_stop,Flag) :-
	line_search_never_stop(Flag).

get_learning_flag(verbosity_level,Number) :-
	verbosity_level(Number).




set_learning_flag(init_method,(Query,Probability,BDDFile,ProbFile,Call)) :-
	retractall(init_method(_,_,_,_,_)),
	assert(init_method(Query,Probability,BDDFile,ProbFile,Call)).


set_learning_flag(rebuild_bdds,Frequency) :-
	integer(Frequency),
	Frequency>=0,
	retractall(rebuild_bdds(_)),
	assert(rebuild_bdds(Frequency)).


set_learning_flag(reuse_initialized_bdds,Flag) :-
	(Flag==true;Flag==false),
	!,
	retractall(reuse_initialized_bdds(_)),
	assert(reuse_initialized_bdds(Flag)).

set_learning_flag(learning_rate,V) :-
	(V=examples -> true;(number(V),V>=0)),
	!,
	retractall(learning_rate(_)),
	assert(learning_rate(V)).

set_learning_flag(probability_initializer,(FactID,Probability,Query)) :-
	var(FactID),
	var(Probability),
	callable(Query),
	retractall(probability_initializer(_,_,_)),
	assert(probability_initializer(FactID,Probability,Query)).

set_learning_flag(check_duplicate_bdds,Flag) :-
	(Flag==true;Flag==false),
	!,
	retractall(check_duplicate_bdds(_)),
	assert(check_duplicate_bdds(Flag)).

set_learning_flag(output_directory,Directory) :-
	(
	    file_exists(Directory)
	->
	    file_property(Directory,type(directory));
	    make_directory(Directory)
	),

	absolute_file_name(Directory,Path),
	atomic_concat([Path,'/'],PathSlash),
	atomic_concat([Path,'/log.dat'],Log_File),
		
	retractall(output_directory(_)),
	assert(output_directory(PathSlash)),
	logger_set_filename(Log_File),
	set_problog_flag(dir,Directory).

set_learning_flag(query_directory,Directory) :-
	(
	    file_exists(Directory)
	->
	    file_property(Directory,type(directory));
	    make_directory(Directory)
	),
	absolute_file_name(Directory,Path),
	atomic_concat([Path,'/'],PathSlash),
	retractall(query_directory(_)),
	assert(query_directory(PathSlash)).

set_learning_flag(log_frequency,Frequency) :-
	integer(Frequency),
	Frequency>=0,
	retractall(log_frequency(_)),
	assert(log_frequency(Frequency)).

set_learning_flag(alpha,Alpha) :-
	(number(Alpha);Alpha==auto),
	!,
	retractall(alpha(_)),
	assert(alpha(Alpha)).
set_learning_flag(sigmoid_slope,Slope) :-
	number(Slope),
	Slope>0,
	retractall(sigmoid_slope(_)),
	assert(sigmoid_slope(Slope)).


set_learning_flag(line_search,Flag) :-
	(Flag==true;Flag==false),
	!,
	retractall(line_search(_)),
	assert(line_search(Flag)).
set_learning_flag(line_search_tolerance,Number) :-
	number(Number),
	Number>0,
	retractall(line_search_tolerance(_)),
	assert(line_search_tolerance(Number)).
set_learning_flag(line_search_interval,(L,R)) :-
	number(L),
	number(R),
	L<R,
	retractall(line_search_interval(_,_)),
	assert(line_search_interval(L,R)).
set_learning_flag(line_search_tau,Number) :-
	number(Number),
	Number>0,
	retractall(line_search_tau(_)),
	assert(line_search_tau(Number)).
set_learning_flag(line_search_never_stop,Flag) :-
	(Flag==true;Flag==false),
	!,
	retractall(line_search_nerver_stop(_)),
	assert(line_search_never_stop(Flag)).

set_learning_flag(verbosity_level,Level) :-
	integer(Level),
	retractall(verbosity_level(_)),
	assert(verbosity_level(Level)),
	(
	 Level<4
	->
	 set_problog_flag(verbose,false);
	 set_problog_flag(verbose,true)
	).
	


%%%%%%%%%%%%%%%%%%%%%%%%
% show values
%%%%%%%%%%%%%%%%%%%%%%%%

skolemize(T1,T2):-
	copy_term(T1,T2),
	numbervars(T2,0,_).

learning_flags :-
	format('~n',[]),
	print_sep_line,
	format('learning flags: use set_learning_flag(Flag,Option) to change, learning_flag(Flag,Option) to view~n',[]),
	print_sep_line,
	print_param(description,value,flag,option),
	print_sep_line,

	learning_flag(output_directory,Output_Directory),
	print_long_param('Where to store results',Output_Directory,'output_directory','path'),

	learning_flag(query_directory,Query_Directory),
	print_long_param('Where to store BDD files',Query_Directory,'query_directory','path'),

	learning_flag(verbosity_level,Verbosity_Level),
	print_param('How much output shall be given (0=nothing,5=all)',Verbosity_Level,'verbosity_level','0,1,..,5'),

	print_sep_line,

	learning_flag(reuse_initialized_bdds,Reuse_Initialized_Bdds),
	print_param('Reuse BDDs from previous runs',Reuse_Initialized_Bdds,'reuse_initialized_bdds','true/false'),

	learning_flag(rebuild_bdds,Rebuild_BDDs),
	print_param('Rebuild BDDs every nth iteration (0=never)',Rebuild_BDDs,'rebuild_bdds','Integer>=0'),
	learning_flag(check_duplicate_bdds,Check_Duplicate_BDDs),
	print_param('Store intermediate results in hash table',Check_Duplicate_BDDs,'check_duplicate_bdds','true/false'),

	learning_flag(init_method,Init_Method),
	skolemize(Init_Method,Init_Method_SK),
	print_long_param('ProbLog predicate to search proofs',Init_Method_SK,'init_method','(+Query,-P,+BDDFile,+ProbFile,+Call)'),

	learning_flag(probability_initializer,Prob_Initializer),
	skolemize(Prob_Initializer,Prob_Initializer_SK),
	print_long_param('Predicate to initialize probabilities',Prob_Initializer_SK,'probability_initializer','(+FactID,-P,+Call)'),

	print_sep_line,


	learning_flag(log_frequency,Log_Frequency),
	print_param('log results every nth iteration',Log_Frequency,'log_frequency','integer>0'),

	learning_flag(alpha,Alpha),
	print_param('weight of negative examples (auto=n_p/n_n)',Alpha,'alpha','number or "auto"'),

	learning_flag(sigmoid_slope,Slope),
	print_param('slope of sigmoid function',Slope,'slope','number>0'),

	print_sep_line,

	
	learning_flag(learning_rate,Learning_Rate),
	print_param('Default Learning rate (If line_search=false)',Learning_Rate,'learning_rate','0<Number or "examples"'),
	learning_flag(line_search,Line_Search),
	print_param('Use line search to estimate learning rate',Line_Search,'line_search','true/false'),
	learning_flag(line_search_tau,Line_Search_Tau),
	print_param('Tau value for line search',Line_Search_Tau,'line_search_tau','0<Number<1'),
	learning_flag(line_search_tolerance,Line_Search_Tolerance),
	print_param('Tolerance value for line search',Line_Search_Tolerance,'line_search_tolerance','0<Number'),
	learning_flag(line_search_interval,Line_Search_Interval),
	print_param('Interval for line search',Line_Search_Interval,'line_search_interval','(a,b) an interval with 0<=a<b'),
	learning_flag(line_search_never_stop,Line_Search_Never_Stop),
	print_param('Make tiny step if line search returns 0',Line_Search_Never_Stop,'line_search_never_stop','true/false'),
	
	print_sep_line,
	
	format('~n',[]),
	flush_output.