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Newest ProbLog version

This commit is contained in:
Theofrastos Mantadelis 2010-12-16 14:30:50 +01:00
parent 9a45897308
commit a442d888de
24 changed files with 739 additions and 757 deletions
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1
packages/ProbLog/dtproblog.yap
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@ -707,6 +707,7 @@ bdd_optimization(N,EV,Decisions,Status) :-
%(problog_flag(verbose,true) -> Debug = ' -d';Debug = ''), % messes up result parsing
atomic_concat([ProblogBDD, Param, ' -l ',BDDFile,' -i ',BDDParFile,' -u ',UtilFile,' -m s',LocalPar,Forest,' -t ', BDDTime,' > ', ResultFile],Command),
statistics(walltime,_),
% format(user,'$ ~w~n',[Command]),
shell(Command,Return),
(Return =\= 0 ->
Status = timeout

58
packages/ProbLog/problog.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-11-23 11:47:48 +0100 (Tue, 23 Nov 2010) $
% $Revision: 5027 $
% $Date: 2010-12-15 11:12:48 +0100 (Wed, 15 Dec 2010) $
% $Revision: 5138 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog
@ -350,16 +350,13 @@
:- use_module('problog/mc_DNF_sampling').
:- use_module('problog/timer').
:- use_module('problog/utils').
:- catch(use_module('problog/ad_converter'),_,true).
:- use_module('problog/ad_converter').
:- catch(use_module('problog/variable_elimination'),_,true).
% op attaching probabilities to facts
:- op( 550, yfx, :: ).
:- op( 550, fx, ?:: ).
% for annotated disjunctions
% :- op(1149, yfx, <-- ).
%%%%%%%%%%%%%%%%%%%%%%%%
% control predicates on various levels
%%%%%%%%%%%%%%%%%%%%%%%%
@ -509,7 +506,7 @@ problog_dir(PD):- problog_path(PD).
%%%%%%%%%%%%%%%%%%%%%%%%
init_global_params :-
%grow_atom_table(1000000),
grow_atom_table(1000000), % this will reserve us some memory, there are cases where you might need more
%%%%%%%%%%%%
% working directory: all the temporary and output files will be located there
@ -591,9 +588,9 @@ generate_atoms(N, A):-
% dynamic predicate problog_predicate(Name,Arity) keeps track of predicates that already have wrapper clause
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% converts annotated disjunctions - if loaded
term_expansion_intern(A, B, C):-
catch(term_expansion_intern_ad(A, B, C), _, false).
% converts annotated disjunctions
term_expansion_intern(A, Module, C):-
term_expansion_intern_ad(A, Module, C).
% converts ?:: prefix to ? :: infix, as handled by other clause
term_expansion_intern((Annotation::Fact), Module, ExpandedClause) :-
@ -667,13 +664,12 @@ term_expansion_intern(Head :: Goal,Module,problog:ProbFact) :-
)
),
copy_term(((X,Distribution) :: Goal), ((X2,Distribution2) :: Goal2)),
% bind_the_variable
X2=Distribution2,
X=Distribution,
% find position in term
Goal2=..[Name|Args],
once(nth1(Pos,Args,Distribution2)),
Goal=..[Name|Args],
once(nth1(Pos,Args,Distribution)),
length(Args,Arity),
atomic_concat([problogcontinuous_,Name],ProblogName),
@ -1165,31 +1161,20 @@ set_continuous_fact_parameters(ID,Parameters) :-
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% writing those facts with learnable parameters to File
% writing all probabilistic and continuous facts to Filename
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
export_facts(Filename) :-
open(Filename,'write',Handle),
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
( % go over all probabilistic facts
P::Goal,
format(Handle,'~w :: ~q.~n',[P,Goal]),
forall(P::Goal,
format(Handle,'~10f :: ~q.~n',[P,Goal])),
fail; % go to next prob. fact
true
),
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
( % go over all continuous facts
continuous_fact(ID),
forall(continuous_fact(ID),
(
get_continuous_fact_parameters(ID,Param),
format(Handle,'~q. % ~q~n',[Param,ID]),
fail; % go to next cont. fact
true
format(Handle,'~q. % ~q~n',[Param,ID])
)
),
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
close(Handle).
@ -1946,13 +1931,11 @@ disjoin_hybrid_proofs([GroundID|T]) :-
intervals_partition(Intervals,Partition),
% go over all proofs where this fact occurs
forall(hybrid_proof(ProofID,ID,GroundID,Interval),
(
hybrid_proof(ProofID,ID,GroundID,Interval),
intervals_disjoin(Interval,Partition,PInterval),
assertz(hybrid_proof_disjoint(ProofID,ID,GroundID,PInterval)),
fail; % go to next proof
true
assertz(hybrid_proof_disjoint(ProofID,ID,GroundID,PInterval))
)
),
disjoin_hybrid_proofs(T).
@ -1996,6 +1979,7 @@ problog_low(_, _, LP, Status) :-
timer_stop(sld_time,SLD_Time),
problog_var_set(sld_time, SLD_Time),
nb_getval(problog_completed_proofs, Trie_Completed_Proofs),
%print_nested_ptree(Trie_Completed_Proofs),
eval_dnf(Trie_Completed_Proofs, LP, Status),
(problog_flag(verbose, true)->
problog_statistics

126
packages/ProbLog/problog/ad_converter.yap
View File

@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-10-13 17:09:47 +0200 (Wed, 13 Oct 2010) $
% $Revision: 4915 $
% $Date: 2010-12-13 18:15:14 +0100 (Mon, 13 Dec 2010) $
% $Revision: 5125 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog
@ -214,51 +214,64 @@
]).
% general yap modules
:- use_module(library(lists),[reverse/2]).
:- use_module(library(lists),[reverse/2,member/2,append/3]).
:- use_module(flags).
:- style_check(all).
:- yap_flag(unknown,error).
:- discontiguous user:ad_intern/2.
:- op( 550, yfx, :: ).
% for annotated disjunctions
:- op(1149, yfx, <-- ).
:- initialization(problog_define_flag(show_ad_compilation,problog_flag_validate_boolean,'show compiled code for ADs',false,annotated_disjunctions)).
:- initialization(problog_define_flag(ad_cpl_semantics,problog_flag_validate_boolean,'use CP-logics semantics for ADs',true,annotated_disjunctions)).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
term_expansion_intern_ad( (Head<--Body),Module,ad_intern((Head<--Body),ID)) :-
proper_tunable_annotated_disjunction(Head),
!,
compile_tunable_annotated_disjunction(Head,Body,Facts,Bodies,ID),
assert_all_ad_facts(Facts,Module),
assert_all_ad_bodies(Bodies,Module).
term_expansion_intern_ad( (Head<--Body),Module,ad_intern((Head<--Body),ID)) :-
problog_flag(ad_cpl_semantics,AD_CPL_Semantics),
(
proper_tunable_annotated_disjunction(Head)
->
compile_tunable_annotated_disjunction(Head,Body,Facts,Bodies,ID,AD_CPL_Semantics);
(
proper_annotated_disjunction(Head),
!,
compile_annotated_disjunction(Head,Body,Facts,Bodies,ID),
assert_all_ad_facts(Facts,Module),
assert_all_ad_bodies(Bodies,Module).
compile_annotated_disjunction(Head,Body,Facts,Bodies,ID,AD_CPL_Semantics)
)
),
forall(member(F,Facts),(once(problog:term_expansion_intern(F,Module,Atom)),
assertz(problog:Atom))),
forall(member(B,Bodies),assertz(Module:B)),
problog_flag(show_ad_compilation,Show_AD_compilation),
(
Show_AD_compilation==true
->
(
format('Compiling the annotated disjunction~n ~q~ninto the following code~n',[(Head<--Body)]),
format('================================================~n',[]),
forall(member(F,Facts),format(' ~q.~n',[F])),
format(' - - - - - - - - - - - - - - - - - - - - - - ~n',[]),
forall(member(B,Bodies),format(' ~q.~n',[B])),
format('================================================~2n',[])
);
true
).
term_expansion_intern_ad( (Head<--Body),_,_) :-
format_to_chars('Error at compiling the annotated disjunction ~q<--Body.',[Head,Body],Error),
print_message(error,Error),
fail.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
assert_all_ad_facts([],_).
assert_all_ad_facts([F|T],Module) :-
once(problog:term_expansion_intern(F,Module,Atom)),
assertz(problog:Atom),
assert_all_ad_facts(T,Module).
assert_all_ad_bodies([],_).
assert_all_ad_bodies([B|T],Module) :-
assertz(Module:B),
assert_all_ad_bodies(T,Module).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
@ -303,22 +316,36 @@ proper_tunable_annotated_disjunction((X;Y)) :-
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
compile_tunable_annotated_disjunction(Head,Body,Facts2,Bodies2,Extra_ID) :-
compile_tunable_annotated_disjunction(Head,Body,Facts2,Bodies2,Extra_ID,AD_CPL_Semantics) :-
get_next_unique_id(Extra_ID),
convert_a_tunable(Head,Extra_ID,[],Facts),
convert_b(Head,Body,_NewBody,Extra_ID,[],Bodies),
(
AD_CPL_Semantics==true
->
term_variables(Body,Body_Vars);
Body_Vars=[]
),
convert_a_tunable(Head,Extra_ID,[],Facts,Body_Vars),
convert_b(Head,Body,_NewBody,Extra_ID,[],Bodies,Body_Vars),
reverse(Facts,Facts2),
reverse(Bodies,Bodies2).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
compile_annotated_disjunction(Head,Body,Facts2,Bodies2,Extra_ID) :-
compile_annotated_disjunction(Head,Body,Facts2,Bodies2,Extra_ID,AD_CPL_Semantics) :-
get_next_unique_id(Extra_ID),
convert_a(Head,0.0,_Acc,Extra_ID,[],Facts),
convert_b(Head,Body,_NewBody,Extra_ID,[],Bodies),
(
AD_CPL_Semantics==true
->
term_variables(Body,Body_Vars);
Body_Vars=[]
),
convert_a(Head,0.0,_Acc,Extra_ID,[],Facts,Body_Vars),
convert_b(Head,Body,_NewBody,Extra_ID,[],Bodies,Body_Vars),
reverse(Facts,Facts2),
reverse(Bodies,Bodies2).
@ -326,16 +353,17 @@ compile_annotated_disjunction(Head,Body,Facts2,Bodies2,Extra_ID) :-
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
convert_a((X;Y),OldAcc,Acc,Extra_ID,OldFacts,Facts) :-
convert_a(X,OldAcc,NewAcc,Extra_ID,OldFacts,NewFacts),
convert_a(Y,NewAcc,Acc,Extra_ID,NewFacts,Facts).
convert_a(P::Atom,OldAcc,NewAcc,Extra_ID,OldFacts,[P1::ProbFact|OldFacts]) :-
convert_a((X;Y),OldAcc,Acc,Extra_ID,OldFacts,Facts,Body_Vars) :-
convert_a(X,OldAcc,NewAcc,Extra_ID,OldFacts,NewFacts,Body_Vars),
convert_a(Y,NewAcc,Acc,Extra_ID,NewFacts,Facts,Body_Vars).
convert_a(P::Atom,OldAcc,NewAcc,Extra_ID,OldFacts,[P1::ProbFact|OldFacts],Body_Vars) :-
Atom =.. [Functor|AllArguments],
append(AllArguments,Body_Vars,NewAllArguments),
length(AllArguments,Arity),
atomic_concat([mvs_fact_,Functor,'_',Arity,'_',Extra_ID],NewAtom),
ProbFact =.. [NewAtom|AllArguments],
ProbFact =.. [NewAtom|NewAllArguments],
(
P=:=0
->
@ -351,29 +379,31 @@ convert_a(P::Atom,OldAcc,NewAcc,Extra_ID,OldFacts,[P1::ProbFact|OldFacts]) :-
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
convert_a_tunable((X;Y),Extra_ID,OldFacts,Facts) :-
convert_a_tunable(X,Extra_ID,OldFacts,NewFacts),
convert_a_tunable(Y,Extra_ID,NewFacts,Facts).
convert_a_tunable(P::Atom,Extra_ID,OldFacts,[P::ProbFact|OldFacts]) :-
convert_a_tunable((X;Y),Extra_ID,OldFacts,Facts,Body_Vars) :-
convert_a_tunable(X,Extra_ID,OldFacts,NewFacts,Body_Vars),
convert_a_tunable(Y,Extra_ID,NewFacts,Facts,Body_Vars).
convert_a_tunable(P::Atom,Extra_ID,OldFacts,[P::ProbFact|OldFacts],Body_Vars) :-
Atom =.. [Functor|AllArguments],
append(AllArguments,Body_Vars,NewAllArguments),
length(AllArguments,Arity),
atomic_concat([mvs_fact_,Functor,'_',Arity,'_',Extra_ID],NewAtom),
ProbFact =.. [NewAtom|AllArguments].
ProbFact =.. [NewAtom|NewAllArguments].
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
convert_b((X;Y),OldBody,Body,ExtraID,OldBodies,Bodies) :-
convert_b(X,OldBody,NewBody,ExtraID,OldBodies,NewBodies),
convert_b(Y,NewBody,Body,ExtraID,NewBodies,Bodies).
convert_b(_::Atom,OldBody,NewBody,Extra_ID,OldBodies,[(Atom:-ThisBody)|OldBodies]) :-
convert_b((X;Y),OldBody,Body,ExtraID,OldBodies,Bodies,Body_Vars) :-
convert_b(X,OldBody,NewBody,ExtraID,OldBodies,NewBodies,Body_Vars),
convert_b(Y,NewBody,Body,ExtraID,NewBodies,Bodies,Body_Vars).
convert_b(_::Atom,OldBody,NewBody,Extra_ID,OldBodies,[(Atom:-ThisBody)|OldBodies],Body_Vars) :-
Atom =.. [Functor|AllArguments],
append(AllArguments,Body_Vars,NewAllArguments),
length(AllArguments,Arity),
atomic_concat([mvs_fact_,Functor,'_',Arity,'_',Extra_ID],NewFunctor),
ProbFact =.. [NewFunctor|AllArguments],
ProbFact =.. [NewFunctor|NewAllArguments],
tuple_append(OldBody,ProbFact,ThisBody),
tuple_append(OldBody,problog_not(ProbFact),NewBody).

4
packages/ProbLog/problog/extlists.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-09-28 21:04:43 +0200 (Tue, 28 Sep 2010) $
% $Revision: 4838 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

4
packages/ProbLog/problog/flags.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-09-28 21:04:43 +0200 (Tue, 28 Sep 2010) $
% $Revision: 4838 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

4
packages/ProbLog/problog/gflags.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-09-28 21:04:43 +0200 (Tue, 28 Sep 2010) $
% $Revision: 4838 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

4
packages/ProbLog/problog/hash_table.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-09-28 21:04:43 +0200 (Tue, 28 Sep 2010) $
% $Revision: 4838 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

4
packages/ProbLog/problog/intervals.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-09-28 21:04:43 +0200 (Tue, 28 Sep 2010) $
% $Revision: 4838 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

4
packages/ProbLog/problog/logger.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-10-11 14:14:11 +0200 (Mon, 11 Oct 2010) $
% $Revision: 4892 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

4
packages/ProbLog/problog/mc_DNF_sampling.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-09-28 21:04:43 +0200 (Tue, 28 Sep 2010) $
% $Revision: 4838 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

191
packages/ProbLog/problog/nestedtries.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-11-03 19:13:53 +0100 (Wed, 03 Nov 2010) $
% $Revision: 4986 $
% $Date: 2010-12-16 13:33:43 +0100 (Thu, 16 Dec 2010) $
% $Revision: 5156 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog
@ -211,9 +211,25 @@
:- module(nestedtries, [nested_trie_to_depth_breadth_trie/4]).
:- use_module(library(ordsets), [list_to_ord_set/2, ord_subset/2]). % this two might be better to do a custom fast implementation
:- use_module(library(lists), [memberchk/2, delete/3]).
:- use_module(library(tries), [trie_to_depth_breadth_trie/6, trie_get_depth_breadth_reduction_entry/1, trie_dup/2, trie_close/1, trie_open/1, trie_replace_nested_trie/3, trie_remove_entry/1, trie_get_entry/2, trie_put_entry/3, trie_traverse/2]).
:- use_module(library(ordsets), [list_to_ord_set/2,
ord_subset/2,
ord_union/3,
ord_intersection/3]).
:- use_module(library(lists), [append/3,
memberchk/2,
delete/3]).
:- use_module(library(tries), [trie_to_depth_breadth_trie/6,
trie_get_depth_breadth_reduction_entry/1,
trie_dup/2,
trie_close/1,
trie_open/1,
trie_replace_nested_trie/3,
trie_remove_entry/1,
trie_get_entry/2,
trie_put_entry/3,
trie_traverse/2,
trie_traverse_mode/1,
trie_usage/4]).
:- use_module(flags, [problog_define_flag/5, problog_flag/2]).
@ -221,18 +237,21 @@
:- yap_flag(unknown,error).
:- initialization((
% problog_define_flag(subset_check, problog_flag_validate_boolean, 'perform subset check in nested tries', true, nested_tries),
problog_define_flag(loop_refine_ancs, problog_flag_validate_boolean, 'refine ancestors if no loop exists', true, nested_tries)
% problog_define_flag(trie_preprocess, problog_flag_validate_boolean, 'perform a preprocess step to nested tries', false, nested_tries),
% problog_define_flag(refine_anclst, problog_flag_validate_boolean, 'refine the ancestor list with their childs', false, nested_tries),
% problog_define_flag(anclst_represent,problog_flag_validate_in_list([list, integer]), 'represent the ancestor list', list, nested_tries)
problog_define_flag(subset_check, problog_flag_validate_boolean, 'perform subset check in nested tries', true, nested_tries),
problog_define_flag(loop_refine_ancs, problog_flag_validate_boolean, 'refine ancestors if no loop exists', true, nested_tries),
problog_define_flag(trie_preprocess, problog_flag_validate_boolean, 'perform a preprocess step to nested tries', false, nested_tries),
problog_define_flag(refine_anclst, problog_flag_validate_boolean, 'refine the ancestor list with their childs', false, nested_tries),
problog_define_flag(anclst_represent,problog_flag_validate_in_list([list, integer]), 'represent the ancestor list', list, nested_tries)
)).
trie_replace_entry(_Trie, Entry, _E, false):-
!, trie_remove_entry(Entry).
trie_replace_entry(_Trie, Entry, E, false):-
trie_get_entry(Entry, Proof),
memberchk(E, Proof), !,
trie_remove_entry(Entry).
trie_replace_entry(Trie, Entry, E, true):-
!, trie_get_entry(Entry, Proof),
trie_get_entry(Entry, Proof),
memberchk(E, Proof), !,
delete(Proof, E, NewProof),
(NewProof == [] ->
trie_delete(Trie),
@ -275,6 +294,12 @@ is_label(Label, ID):-
Label = not(NestedLabel),
is_label(NestedLabel, ID).
simplify(not(false), true):- !.
simplify(not(true), false):- !.
simplify(not(not(A)), B):-
!, simplify(A, B).
simplify(A, A).
% Ancestor related stuff
initialise_ancestors(0):-
@ -289,6 +314,13 @@ add_to_ancestors(ID, Ancestors, NewAncestors):-
is_list(Ancestors),
list_to_ord_set([ID|Ancestors], NewAncestors).
ancestors_union(Ancestors1, Ancestors2, NewAncestors):-
integer(Ancestors1), !,
NewAncestors is Ancestors1 \/ Ancestors2.
ancestors_union(Ancestors1, Ancestors2, NewAncestors):-
is_list(Ancestors1),
ord_union(Ancestors1, Ancestors2, NewAncestors).
ancestor_subset_check(SubAncestors, Ancestors):-
integer(SubAncestors), !,
SubAncestors is Ancestors /\ SubAncestors.
@ -302,17 +334,61 @@ ancestor_loop_refine(Loop, Ancestors, []):-
var(Loop), is_list(Ancestors), !.
ancestor_loop_refine(true, Ancestors, Ancestors).
ancestor_child_refine(true, Ancestors, Childs, NewAncestors):-
integer(Ancestors), !,
NewAncestors is Ancestors /\ Childs.
ancestor_child_refine(true, Ancestors, Childs, NewAncestors):-
is_list(Ancestors), !,
ord_intersection(Ancestors, Childs, NewAncestors).
ancestor_child_refine(false, Ancestors, _, Ancestors).
% Cycle check related stuff
% missing synonym check
cycle_check(ID, Ancestors):-
get_negated_synonym_id(ID, SynID),
cycle_check_intern(SynID, Ancestors).
cycle_check_intern(ID, Ancestors):-
integer(Ancestors), !,
Bit is 1 << (ID - 1),
Bit is Bit /\ Ancestors.
cycle_check(ID, Ancestors):-
cycle_check_intern(ID, Ancestors):-
is_list(Ancestors),
memberchk(ID, Ancestors).
get_negated_synonym_id(ID, ID).
get_negated_synonym_id(ID, NegID):-
tabling:has_synonyms,
recorded(problog_table, store(Pred, ID, _, _, _), _),
Pred =.. [Name0|Args],
atomic_concat(problog_, Name1, Name0),
atomic_concat(Name, '_original', Name1),
get_negated_name(Name, NotName1),
atomic_concat([problog_, NotName1, '_original'], NotName),
NegPred =.. [NotName|Args],
recorded(problog_table, store(NegPred, NegID, _, _, _), _).
get_negated_name(Name, NotName1):-
recorded(problog_table_synonyms, negated(Name, NotName1), _), !.
get_negated_name(Name, NotName1):-
recorded(problog_table_synonyms, negated(NotName1, Name), _).
trie_dup_reverse(Trie, DupTrie):-
trie_open(DupTrie),
trie_traverse_mode(backward),
trie_dup_rev(Trie, DupTrie),
trie_traverse_mode(forward).
trie_dup_rev(Trie, DupTrie):-
\+ trie_usage(Trie, 0, 0, 0),
trie_traverse(Trie, Entry),
trie_get_entry(Entry, Term),
trie_put_entry(DupTrie, Term, _),
fail.
trie_dup_rev(_, _).
preprocess(Index, DepthBreadthTrie, OptimizationLevel, StartCount, FinalEndCount):-
problog:problog_chktabled(Index, Trie), !,
trie_dup(Trie, CopyTrie),
@ -332,7 +408,7 @@ make_nested_trie_base_cases(Trie, t(ID), DepthBreadthTrie, OptimizationLevel, St
make_nested_trie_base_cases(Trie, t(ID), DepthBreadthTrie, OptimizationLevel, EndCount, FinalEndCount, NewAncestors)
;
FinalEndCount = EndCount,
get_set_trie(ID, Label, Ancestors)
set_trie(ID, Label, Ancestors)
).
nested_trie_to_depth_breadth_trie(Trie, DepthBreadthTrie, FinalLabel, OptimizationLevel):-
@ -344,80 +420,69 @@ nested_trie_to_depth_breadth_trie(Trie, DepthBreadthTrie, FinalLabel, Optimizati
StartCount = 0
),
initialise_ancestors(Ancestors),
% initialise_ancestors(Childs),
(problog_flag(loop_refine_ancs, true) ->
trie_2_dbtrie_init(Trie, DepthBreadthTrie, OptimizationLevel, StartCount, _, Ancestors, FinalLabel, _)
trie_2_dbtrie_init(Trie, DepthBreadthTrie, OptimizationLevel, StartCount, _, Ancestors, FinalLabel, _, _Childs)
;
trie_2_dbtrie_init(Trie, DepthBreadthTrie, OptimizationLevel, StartCount, _, Ancestors, FinalLabel, true)
trie_2_dbtrie_init(Trie, DepthBreadthTrie, OptimizationLevel, StartCount, _, Ancestors, FinalLabel, true, _Childs)
),
eraseall(problog_trie_table).
trie_2_dbtrie_init(ID, DepthBreadthTrie, OptimizationLevel, StartCount, EndCount, Ancestors, Label, ContainLoop):-
trie_2_dbtrie_init(ID, DepthBreadthTrie, OptimizationLevel, StartCount, EndCount, Ancestors, Label, ContainLoop, FinalChilds):-
initialise_ancestors(Childs),
get_trie_pointer(ID, Trie),
trie_dup(Trie, CopyTrie),
trie_2_dbtrie_intern(CopyTrie, DepthBreadthTrie, OptimizationLevel, StartCount, EndCount, Ancestors, Label, ContainLoop),
trie_dup_reverse(Trie, CopyTrie),
trie_2_dbtrie_intern(CopyTrie, DepthBreadthTrie, OptimizationLevel, StartCount, EndCount, Ancestors, Label, ContainLoop, Childs, FinalChilds),
trie_close(CopyTrie).
trie_2_dbtrie_intern(Trie, DepthBreadthTrie, OptimizationLevel, StartCount, FinalEndCount, Ancestors, TrieLabel, ContainLoop):-
trie_2_dbtrie_intern(Trie, DepthBreadthTrie, OptimizationLevel, StartCount, FinalEndCount, Ancestors, TrieLabel, ContainLoop, Childs, FinalChilds):-
trie_to_depth_breadth_trie(Trie, DepthBreadthTrie, Label, OptimizationLevel, StartCount, EndCount),
(is_trie(Label, ID) -> % Label might have issues with negation
(is_trie(Label, ID) ->
problog_flag(refine_anclst, ChildRefineAncestors),
trie_get_depth_breadth_reduction_entry(NestedEntry),
% check if Trie introduces a loop
(cycle_check(ID, Ancestors) ->
ContainLoop = true,
NewLabel = false,
NewEndCount = EndCount,
initialise_ancestors(GrandChilds)
; get_trie(ID, NewLabel, Ancestors) ->
GrandChilds = Ancestors,
NewEndCount = EndCount
;
% check if Trie is resolved and extract it
(get_set_trie(ID, NewLabel, Ancestors) ->
NewEndCount = EndCount
;
% calculate the nested trie
add_to_ancestors(ID, Ancestors, NewAncestors), % to be able to support 2 representations
trie_2_dbtrie_init(ID, DepthBreadthTrie, OptimizationLevel, EndCount, NewEndCount, NewAncestors, NewLabel, NewContainLoop),
ancestor_loop_refine(NewContainLoop, Ancestors, RefinedAncestors),
get_set_trie(ID, NewLabel, RefinedAncestors),
add_to_ancestors(ID, Ancestors, NewAncestors),
trie_2_dbtrie_init(ID, DepthBreadthTrie, OptimizationLevel, EndCount, NewEndCount, NewAncestors, DerefLabel, NewContainLoop, GrandChilds),
ancestor_loop_refine(NewContainLoop, Ancestors, RefinedAncestors1),
ancestor_child_refine(ChildRefineAncestors, RefinedAncestors1, GrandChilds, RefinedAncestors),
simplify(DerefLabel, NewLabel),
set_trie(ID, NewLabel, RefinedAncestors),
ContainLoop = NewContainLoop
)
),
trie_replace_entry(Trie, NestedEntry, t(ID), NewLabel), % should be careful to verify that it works also with not(t(ID))
trie_2_dbtrie_intern(Trie, DepthBreadthTrie, OptimizationLevel, NewEndCount, FinalEndCount, Ancestors, TrieLabel, ContainLoop)
trie_replace_entry(Trie, NestedEntry, t(ID), NewLabel),
(ChildRefineAncestors ->
add_to_ancestors(ID, Childs, NewChilds1),
ancestors_union(NewChilds1, GrandChilds, NewChilds)
;
NewChilds = Childs
),
trie_2_dbtrie_intern(Trie, DepthBreadthTrie, OptimizationLevel, NewEndCount, FinalEndCount, Ancestors, TrieLabel, ContainLoop, NewChilds, FinalChilds)
;
% else we can terminate and return
FinalEndCount = EndCount,
TrieLabel = Label
TrieLabel = Label,
FinalChilds = Childs
).
% predicate to check/remember resolved tries
% no refiment of ancestor list included
get_trie_pointer(ID, Trie):-
problog:problog_chktabled(ID, Trie), !.
get_trie_pointer(Trie, Trie).
get_set_trie(Trie, Label, Ancestors):-
get_trie(Trie, Label, Ancestors):-
problog_flag(subset_check, true), !,
recorded(problog_trie_table, store(Trie, StoredAncestors, Label), _),
(problog_flag(subset_check, true) ->
ancestor_subset_check(StoredAncestors, Ancestors)
;
StoredAncestors == Ancestors
), !.
get_set_trie(Trie, Label, Ancestors):-
ground(Label),
ancestor_subset_check(StoredAncestors, Ancestors).
get_trie(Trie, Label, Ancestors):-
recorded(problog_trie_table, store(Trie, StoredAncestors, Label), _),
StoredAncestors == Ancestors.
set_trie(Trie, Label, Ancestors):-
recordz(problog_trie_table, store(Trie, Ancestors, Label), _).
% chk_negated([H|T], ID):-
% simplify(H, not(t(ID))), !.
% chk_negated([_|T], ID):-
% chk_negated(T, ID).
/*
chk_negated([], ID, ID).
chk_negated([H|T], ID, not(ID)):-
simplify(H, not(t(ID))), !.
chk_negated([H|T], ID, ID):-
simplify(H, t(ID)), !.
chk_negated([_|T], ID, FID):-
chk_negated(T, ID, FID).*/

4
packages/ProbLog/problog/os.yap
View File

@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-11-29 10:58:04 +0100 (Mon, 29 Nov 2010) $
% $Revision: 5029 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

4
packages/ProbLog/problog/print.yap
View File

@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-10-06 12:56:13 +0200 (Wed, 06 Oct 2010) $
% $Revision: 4877 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

4
packages/ProbLog/problog/print_learning.yap
View File

@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-09-28 21:04:43 +0200 (Tue, 28 Sep 2010) $
% $Revision: 4838 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

41
packages/ProbLog/problog/ptree.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-12-02 14:35:05 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5041 $
% $Date: 2010-12-16 13:33:43 +0100 (Thu, 16 Dec 2010) $
% $Revision: 5156 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog
@ -282,12 +282,7 @@
problog_define_flag(use_naive_trie, problog_flag_validate_boolean, 'use the naive algorithm to generate bdd scripts', false),
problog_define_flag(use_old_trie, problog_flag_validate_boolean, 'use the old trie 2 trie transformation no nested', true),
problog_define_flag(use_dec_trie, problog_flag_validate_boolean, 'use the decomposition method', false),
problog_define_flag(subset_check, problog_flag_validate_boolean, 'perform subset check in nested tries', true),
problog_define_flag(deref_terms, problog_flag_validate_boolean, 'deref BDD terms after last use', false),
problog_define_flag(trie_preprocess, problog_flag_validate_boolean, 'perform a preprocess step to nested tries', false),
problog_define_flag(refine_anclst, problog_flag_validate_boolean, 'refine the ancestor list with their childs', false),
problog_define_flag(anclst_represent,problog_flag_validate_in_list([list, integer]), 'represent the ancestor list', list)
problog_define_flag(deref_terms, problog_flag_validate_boolean, 'deref BDD terms after last use', false)
)).
@ -1252,6 +1247,8 @@ add_to_vars(V):-
variables_in_dbtrie(Trie, []):-
empty_ptree(Trie), !.
variables_in_dbtrie(Trie, []):-
trie_check_entry(Trie, [true], _R), !.
variables_in_dbtrie(Trie, L):-
all(V, variable_in_dbtrie(Trie,V), L).
@ -1339,10 +1336,11 @@ is_state(false).
nested_trie_to_bdd_trie(A, B, OutputFile, OptimizationLevel, FileParam):-
% trie_nested_to_depth_breadth_trie(A, B, LL, OptimizationLevel, problog:problog_chktabled),
nested_trie_to_depth_breadth_trie(A, B, LL, OptimizationLevel),
(is_label(LL) ->
simplify(LL, FLL),
(is_label(FLL) ->
retractall(deref(_,_)),
(problog_flag(deref_terms, true) ->
asserta(deref(LL,no)),
asserta(deref(FLL,no)),
mark_for_deref(B),
V = 3
;
@ -1358,7 +1356,7 @@ nested_trie_to_bdd_trie(A, B, OutputFile, OptimizationLevel, FileParam):-
write('@BDD'), write(V), nl,
write(VarCNT), nl,
write(0), nl,
(LL = not(NegL)->
(FLL = not(NegL)->
atomic_concat('L', NegStep, NegL),
number_atom(NegStepN, NegStep),
InterStep is NegStepN + 1,
@ -1368,19 +1366,18 @@ nested_trie_to_bdd_trie(A, B, OutputFile, OptimizationLevel, FileParam):-
write(FL), write(' = ~'), write(NegL), nl,
write(FL), nl
;
atomic_concat('L', InterStep, LL),
atomic_concat('L', InterStep, FLL),
write(InterStep), nl,
trie_write(B, LL),
write(LL), nl
trie_write(B, FLL),
write(FLL), nl
),
told
;
(is_state(LL) ->
(is_state(FLL) ->
Edges = []
;
Edges = [LL]
Edges = [FLL]
),
writeln(Edges),
tell(FileParam),
simplify_list(Edges, SEdges),
bdd_vars_script(SEdges),
@ -1390,12 +1387,11 @@ nested_trie_to_bdd_trie(A, B, OutputFile, OptimizationLevel, FileParam):-
write(1), nl,
write(0), nl,
write(1), nl,
(LL = not(_) ->
(FLL = not(_) ->
write('L1 = ~')
;
write('L1 = ')
),
simplify(LL, FLL),
get_var_name(FLL, NLL),
write(NLL),nl,
write('L1'), nl,
@ -1830,6 +1826,7 @@ ptree_decomposition(Trie, BDDFileName, VarFileName) :-
tmpnam(TmpFile1),
nb_setval(next_inter_step, 1),
variables_in_dbtrie(Trie, T),
length(T, VarCnt),
tell(VarFileName),
bdd_vars_script(T),
@ -1860,6 +1857,9 @@ get_next_inter_step(I):-
decompose_trie(Trie, _, false):-
empty_ptree(Trie), !.
decompose_trie(Trie, _, 'TRUE'):-
trie_check_entry(Trie, [true], _R),!.
decompose_trie(Trie, [H|[]], Var):-
trie_usage(Trie, 1, _, _),
get_var_name(H, VarA),
@ -1871,9 +1871,6 @@ decompose_trie(Trie, [H|[]], Var):-
),
!.
decompose_trie(Trie, _, 'TRUE'):-
trie_check_entry(Trie, [true], _R),!.
decompose_trie(Trie, [H|_T], L3):-
trie_open(TrieWith),
trie_open(TrieWithNeg),

4
packages/ProbLog/problog/sampling.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-09-28 21:04:43 +0200 (Tue, 28 Sep 2010) $
% $Revision: 4838 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

18
packages/ProbLog/problog/tabling.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-11-09 15:09:33 +0100 (Tue, 09 Nov 2010) $
% $Revision: 4992 $
% $Date: 2010-12-13 16:29:18 +0100 (Mon, 13 Dec 2010) $
% $Revision: 5122 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog
@ -298,12 +298,6 @@ problog_table_next_index(Index):-
NIndex is Index + 1,
nb_setval(problog_tabling_next_index, NIndex).
makeargs(0, []):-!.
makeargs(N, [_Arg|L]):-
N > 0,
NN is N - 1,
makeargs(NN, L).
problog_table(M:P) :- !,
problog_table(P, M).
problog_table(P) :-
@ -316,12 +310,12 @@ problog_table((P1, P2), M) :-
problog_table(P1, M),
problog_table(P2, M).
problog_table(Name/Arity, Module) :-
makeargs(Arity, Args),
length(Args,Arity),
Head =.. [Name|Args],
\+ predicate_property(Module:Head, dynamic), !,
throw(error('problog_table: Problog tabling currently requires the predicate to be declared dynamic and compiles it to static.')).
problog_table(Name/Arity, Module) :-
makeargs(Arity, Args),
length(Args,Arity),
Head =.. [Name|Args],
atom_concat(['problog_', Name, '_original'], OriginalName),
atom_concat(['problog_', Name, '_mctabled'], MCName),
@ -413,8 +407,8 @@ problog_table(Name/Arity, Module) :-
erase(Ref),
(empty_ptree(HashTrie) ->
recordz(problog_table, store(OriginalPred, Hash, HashTrie, SuspTrie, fail), _NRef),
delete_ptree(SuspTrie),
fail % no justification exists
delete_ptree(SuspTrie) %,
%fail % no justification exists
;
recordz(problog_table, store(OriginalPred, Hash, HashTrie, SuspTrie, true), _NRef),
merge_ptree(HashTrie, SuspTrie),

4
packages/ProbLog/problog/timer.yap
View File

@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-10-15 17:09:55 +0200 (Fri, 15 Oct 2010) $
% $Revision: 4939 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

77
packages/ProbLog/problog/utils.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-12-02 14:35:05 +0100 (Thu, 02 Dec 2010) $
% $Revision: -1 $
% $Date: 2010-12-15 15:52:58 +0100 (Wed, 15 Dec 2010) $
% $Revision: 5144 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog
@ -211,20 +211,21 @@
slice_n/4,
sorted_overlap_test/2,
prefix_bdd_file_with_header/4,
split_list/3]).
split_list/3,
succeeds_n_times/2,
sum_forall/3]).
:- use_module(library(system), [delete_file/1]).
% load swi library, at some point vitor will make swi_expand_file_name/2 a built-in
:- load_foreign_files([libplstream], [], initIO).
% load our own modules
:- use_module(os).
:- meta_predicate succeeds_n_times(0,?), sum_forall(?,:,?).
%========================================================================
%=
%=
%= deletes File, if it doesn't exists, it will succeed silently
%= delete_file_silently(+File)
%========================================================================
delete_file_silently(File) :-
@ -232,9 +233,10 @@ delete_file_silently(File) :-
!.
delete_file_silently(_).
%========================================================================
%=
%=
%= delete all the files in the list silently
%= delete_files_silently(+List)
%========================================================================
delete_files_silently([]).
@ -242,23 +244,25 @@ delete_files_silently([H|T]) :-
delete_file_silently(H),
delete_files_silently(T).
%========================================================================
%= delete all the files matching a certain pattern silently
%= i.e. delete_file_pattern_silently('~/a_path/b_path/','*.txt')
%=
%=
%= delete_file_pattern_silently(+Path,+Pattern)
%========================================================================
delete_file_pattern_silently(Path,Pattern) :-
concat_path_with_filename(Path,Pattern,AbsolutePattern),
swi_expand_file_name(AbsolutePattern,Files),
expand_file_name(AbsolutePattern,Files),
delete_files_silently(Files).
%========================================================================
%= Split a list into the first n elements and the tail
%= +List +Integer -Prefix -Residuum
%= slice_n(+List, +Integer, -Prefix, -Residuum)
%========================================================================
slice_n([],_,[],[]) :-
!.
slice_n([H|T],N,[H|T2],T3) :-
@ -268,9 +272,11 @@ slice_n([H|T],N,[H|T2],T3) :-
slice_n(T,N2,T2,T3).
slice_n(L,0,[],L).
%========================================================================
%= succeeds if the variable V appears exactly once in the term T
%========================================================================
variable_in_term_exactly_once(T,V) :-
term_variables(T,Vars),
var_memberchk_once(Vars,V).
@ -287,6 +293,7 @@ var_memberchk_none([H|T],V) :-
var_memberchk_none(T,V).
var_memberchk_none([],_).
%========================================================================
%= sorted_overlap_test(+L1,+L2)
%= L1 and L2 are ground sorted lists
@ -314,7 +321,7 @@ sorted_overlap_test([_|T1],[H2|T2]) :-
prefix_bdd_file_with_header(BDD_File_Name,VarCount,IntermediateSteps,TmpFile) :-
open(BDD_File_Name,write,H),
% this is the header of the BDD script for problogbdd
format(H, '@BDD1~n~q~n0~n~q~n',[VarCount,IntermediateSteps]),
format(H, '@BDD1~n~w~n0~n~w~n',[VarCount,IntermediateSteps]),
% append the content of the file TmpFile
open(TmpFile,read,H2),
@ -333,12 +340,15 @@ prefix_bdd_file_with_header(BDD_File_Name,VarCount,IntermediateSteps,TmpFile) :-
%========================================================================
%= Split the list L in the two lists L1 and L2 such that
%= append(L1,L2,L) holds.
%=
%= if length of L is even, then L1 and L2 will have the same length
%= if length of L is odd, then L1 will be one element longer than L2
%=
%=
%= split_list(+L,-L1,-L2)
%========================================================================
split_list([],[],[]).
split_list([H|T],L1,L2) :-
length([H|T],Len),
@ -350,3 +360,34 @@ split_list_intern(N,[H|T],[H|T1],L) :-
N>0,
N2 is N-1,
split_list_intern(N2,T,T1,L).
%========================================================================
%= Counts how often Goal succeeds
%= (taken from the YAP manual)
%========================================================================
succeeds_n_times(Goal, Times) :-
Counter = counter(0),
( Goal,
arg(1, Counter, N0),
N is N0 + 1,
nb_setarg(1, Counter, N),
fail
; arg(1, Counter, Times)
).
%========================================================================
%=
%=
%========================================================================
sum_forall(X,Goal, Sum) :-
Temp = sum(0),
( Goal,
arg(1, Temp, Sum0),
Sum is Sum0+X,
nb_setarg(1, Temp, Sum),
fail
; arg(1, Temp, Sum)
).

55
packages/ProbLog/problog/utils_learning.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-12-02 14:35:05 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5041 $
% $Date: 2010-12-14 20:30:07 +0100 (Tue, 14 Dec 2010) $
% $Revision: 5134 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog
@ -209,7 +209,10 @@
create_known_values_file_name/2,
create_bdd_file_name/3,
create_bdd_input_file_name/2,
create_bdd_output_file_name/4]).
create_bdd_output_file_name/4,
create_factprobs_file_name/2,
create_test_predictions_file_name/2,
create_training_predictions_file_name/2]).
@ -249,10 +252,7 @@ empty_output_directory :-
delete_file_pattern_silently(Path,'values_*'),
delete_file_pattern_silently(Path,'factprobs_*'),
delete_file_pattern_silently(Path,'input_*'),
delete_file_pattern_silently(Path,'trainpredictions_*'),
delete_file_pattern_silently(Path,'testpredictions_*'),
delete_file_pattern_silently(Path,'predictions_*').
empty_output_directory :-
throw(error(problog_flag_does_not_exist(output_directory))).
@ -312,3 +312,46 @@ create_bdd_input_file_name(Iteration,Absolute_File_Name) :-
concat_path_with_filename(Path,File_Name,Absolute_File_Name).
create_bdd_input_file_name(_,_) :-
throw(error(problog_flag_does_not_exist(output_directory))).
%========================================================================
%=
%=
%========================================================================
create_factprobs_file_name(Iteration,Absolute_File_Name) :-
problog_flag(output_directory,Path),
!,
atomic_concat(['factprobs_',Iteration,'.pl'],File_Name),
concat_path_with_filename(Path,File_Name,Absolute_File_Name).
create_factprobs_file_name(_,_) :-
throw(error(problog_flag_does_not_exist(output_directory))).
%========================================================================
%=
%=
%========================================================================
create_test_predictions_file_name(Iteration,Absolute_File_Name) :-
problog_flag(output_directory,Path),
!,
atomic_concat(['predictions_test_',Iteration,'.pl'],File_Name),
concat_path_with_filename(Path,File_Name,Absolute_File_Name).
create_test_predictions_file_name(_,_) :-
throw(error(problog_flag_does_not_exist(output_directory))).
%========================================================================
%=
%=
%========================================================================
create_training_predictions_file_name(Iteration,Absolute_File_Name) :-
problog_flag(output_directory,Path),
!,
atomic_concat(['predictions_training_',Iteration,'.pl'],File_Name),
concat_path_with_filename(Path,File_Name,Absolute_File_Name).
create_training_predictions_file_name(_,_) :-
throw(error(problog_flag_does_not_exist(output_directory))).

4
packages/ProbLog/problog/variable_elimination.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-09-28 21:04:43 +0200 (Tue, 28 Sep 2010) $
% $Revision: 4838 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

4
packages/ProbLog/problog/variables.yap
View File

@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-09-28 21:04:43 +0200 (Tue, 28 Sep 2010) $
% $Revision: 4838 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

4
packages/ProbLog/problog/version_control.yap
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@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-10-05 18:15:57 +0200 (Tue, 05 Oct 2010) $
% $Revision: 4876 $
% $Date: 2010-12-02 15:20:15 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5043 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog

435
packages/ProbLog/problog_learning.yap
View File

@ -2,8 +2,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2010-12-02 14:35:05 +0100 (Thu, 02 Dec 2010) $
% $Revision: 5041 $
% $Date: 2010-12-15 15:05:44 +0100 (Wed, 15 Dec 2010) $
% $Revision: 5142 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog
@ -216,7 +216,7 @@
% load modules from the YAP library
:- use_module(library(lists), [max_list/2, min_list/2, sum_list/2]).
:- use_module(library(system), [delete_file/1, file_exists/1, shell/2]).
:- use_module(library(system), [file_exists/1, shell/2]).
% load our own modules
:- use_module(problog).
@ -226,6 +226,7 @@
:- use_module('problog/print_learning').
:- use_module('problog/utils_learning').
:- use_module('problog/utils').
:- use_module('problog/tabling').
% used to indicate the state of the system
:- dynamic(values_correct/0).
@ -256,76 +257,14 @@ user:test_example(A,B,C,=) :-
%========================================================================
%= store the facts with the learned probabilities to a file
%= if F is a variable, a filename based on the current iteration is used
%=
%========================================================================
save_model:-
current_iteration(Iteration),
atomic_concat(['factprobs_',Iteration,'.pl'],Filename),
problog_flag(output_directory,Dir),
concat_path_with_filename(Dir,Filename,Filename2),
export_facts(Filename2).
create_factprobs_file_name(Iteration,Filename),
export_facts(Filename).
%========================================================================
%= store the current succes probabilities for training and test examples
%=
%========================================================================
save_predictions:-
current_iteration(Iteration),
atomic_concat(['predictions_',Iteration,'.pl'],Filename),
problog_flag(output_directory,Dir),
concat_path_with_filename(Dir,Filename,Filename2),
open(Filename2,'append',Handle),
format(Handle,"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n",[]),
format(Handle,"% Iteration, train/test, QueryID, Query, GroundTruth, Prediction %\n",[]),
format(Handle,"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n",[]),
!,
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% start save prediction test examples
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
( % go over all test examples
current_predicate(user:test_example/4),
user:test_example(Query_ID,Query,TrueQueryProb,_),
query_probability(Query_ID,LearnedQueryProb),
format(Handle,'ex(~q,test,~q,~q,~10f,~10f).\n',
[Iteration,Query_ID,Query,TrueQueryProb,LearnedQueryProb]),
fail; % go to next test example
true
),
!,
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% stop save prediction test examples
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% start save prediction training examples
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
( % go over all training examples
current_predicate(user:example/4),
user:example(Query_ID,Query,TrueQueryProb,_),
query_probability(Query_ID,LearnedQueryProb),
format(Handle,'ex(~q,train,~q,~q,~10f,~10f).\n',
[Iteration,Query_ID,Query,TrueQueryProb,LearnedQueryProb]),
fail; % go to next training example
true
),
!,
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% stop save prediction training examples
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
format(Handle,'~3n',[]),
close(Handle).
%========================================================================
@ -339,7 +278,7 @@ check_examples :-
% Check example IDs
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
(
(current_predicate(user:example/4),user:example(ID,_,_,_), \+ atomic(ID))
(user:example(ID,_,_,_), \+ atomic(ID))
->
(
format(user_error,'The example id of training example ~q ',[ID]),
@ -349,7 +288,7 @@ check_examples :-
),
(
(current_predicate(user:test_example/4),user:test_example(ID,_,_,_), \+ atomic(ID))
(user:test_example(ID,_,_,_), \+ atomic(ID))
->
(
format(user_error,'The example id of test example ~q ',[ID]),
@ -362,7 +301,7 @@ check_examples :-
% Check example probabilities
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
(
(current_predicate(user:example/4),user:example(ID,_,P,_), (\+ number(P); P>1 ; P<0))
(user:example(ID,_,P,_), (\+ number(P); P>1 ; P<0))
->
(
format(user_error,'The training example ~q does not have a valid probability value (~q).~n',[ID,P]),
@ -371,7 +310,7 @@ check_examples :-
),
(
(current_predicate(user:test_example/4),user:test_example(ID,_,P,_), (\+ number(P); P>1 ; P<0))
(user:test_example(ID,_,P,_), (\+ number(P); P>1 ; P<0))
->
(
format(user_error,'The test example ~q does not have a valid probability value (~q).~n',[ID,P]),
@ -387,22 +326,18 @@ check_examples :-
(
(
(
current_predicate(user:example/4),
user:example(ID,QueryA,_,_),
user:example(ID,QueryB,_,_),
QueryA \= QueryB
) ;
(
current_predicate(user:test_example/4),
user:test_example(ID,QueryA,_,_),
user:test_example(ID,QueryB,_,_),
QueryA \= QueryB
);
(
current_predicate(user:example/4),
current_predicate(user:test_example/4),
user:example(ID,QueryA,_,_),
user:test_example(ID,QueryB,_,_),
QueryA \= QueryB
@ -419,9 +354,7 @@ check_examples :-
%========================================================================
reset_learning :-
retractall(current_iteration(_)),
retractall(learning_initialized),
retractall(values_correct),
retractall(current_iteration(_)),
retractall(example_count(_)),
@ -474,7 +407,6 @@ do_learning_intern(Iterations,Epsilon) :-
logger_set_variable(iteration,CurrentIteration),
logger_start_timer(duration),
mse_testset,
ground_truth_difference,
gradient_descent,
@ -484,10 +416,7 @@ do_learning_intern(Iterations,Epsilon) :-
(
( Log_Frequency>0, 0 =:= CurrentIteration mod Log_Frequency)
->
(
once(save_predictions),
once(save_model)
);
once(save_model);
true
),
@ -583,55 +512,29 @@ init_learning :-
)
->
(
format('Theory uses continuous facts.~nWill use problog_exact/3 as initalization method.~2n',[]),
format_learning(2,'Theory uses continuous facts.~nWill use problog_exact/3 as initalization method.~2n',[]),
set_problog_flag(init_method,(Query,Probability,BDDFile,ProbFile,problog_exact_save(Query,Probability,_Status,BDDFile,ProbFile)))
);
true
),
(
problog_tabled(_)
->
(
format_learning(2,'Theory uses tabling.~nWill use problog_exact/3 as initalization method.~2n',[]),
set_problog_flag(init_method,(Query,Probability,BDDFile,ProbFile,problog_exact_save(Query,Probability,_Status,BDDFile,ProbFile)))
);
true
),
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% start count test examples
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
bb_put(test_examples,0),
( % go over all test examples
current_predicate(user:test_example/4),
user:test_example(_,_,_,_),
bb_get(test_examples, OldCounter),
NewCounter is OldCounter+1,
bb_put(test_examples,NewCounter),
fail; % go to next text example
true
),
bb_delete(test_examples,TestExampleCount),
succeeds_n_times(user:example(_,_,_,_),TestExampleCount),
format_learning(3,'~q test examples~n',[TestExampleCount]),
!,
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% stop count test examples
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% start count training examples
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
bb_put(training_examples,0),
( % go over all training examples
current_predicate(user:example/4),
user:example(_,_,_,_),
bb_get(training_examples, OldCounter),
NewCounter is OldCounter+1,
bb_put(training_examples,NewCounter),
fail; %go to next training example
true
),
bb_delete(training_examples,TrainingExampleCount),
succeeds_n_times(user:example(_,_,_,_),TrainingExampleCount),
assertz(example_count(TrainingExampleCount)),
format_learning(3,'~q training examples~n',[TrainingExampleCount]),
!,
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% stop count training examples
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@ -647,8 +550,17 @@ init_learning :-
(
problog_flag(alpha,auto)
->
auto_alpha;
true
(
(user:example(_,_,P,_),P<1,P>0)
->
set_problog_flag(alpha,1.0);
(
succeed_n_times((user:example(_,_,P,=),P=:=1.0),Pos_Count),
succeed_n_times((user:example(_,_,P,=),P=:=0.0),Neg_Count),
Alpha is Pos_Count/Neg_Count,
set_problog_flag(alpha,Alpha)
)
)
),
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@ -675,33 +587,16 @@ init_learning :-
init_queries :-
format_learning(2,'Build BDDs for examples~n',[]),
( % go over all test examples
current_predicate(user:test_example/4),
user:test_example(ID,Query,Prob,_),
format_learning(3,' test example ~q: ~q~n',[ID,Query]),
flush_output(user),
init_one_query(ID,Query,test),
fail; % go to next test example
true
),
( % go over all training examples
current_predicate(user:example/4),
user:example(ID,Query,Prob,_),
format_learning(3,' training example ~q: ~q~n',[ID,Query]),
flush_output(user),
init_one_query(ID,Query,training),
fail; %go to next training example
true
).
forall(user:test_example(ID,Query,_Prob,_),init_one_query(ID,Query,test)),
forall(user:example(ID,Query,_Prob,_),init_one_query(ID,Query,training)).
bdd_input_file(Filename) :-
problog_flag(output_directory,Dir),
concat_path_with_filename(Dir,'input.txt',Filename).
init_one_query(QueryID,Query,Type) :-
format_learning(3,' ~q example ~q: ~q~n',[Type,QueryID,Query]),
bdd_input_file(Probabilities_File),
problog_flag(bdd_directory,Query_Directory),
@ -718,7 +613,7 @@ init_one_query(QueryID,Query,Type) :-
(
problog_flag(init_method,(Query,_Prob,Filename,Probabilities_File,Call)),
once(Call),
delete_file(Probabilities_File)
delete_file_silently(Probabilities_File)
)
),
@ -774,27 +669,19 @@ update_values :-
open(Probabilities_File,'write',Handle),
( % go over all probabilistic facts
get_fact_probability(ID,Prob),
forall(get_fact_probability(ID,Prob),
(
inv_sigmoid(Prob,Value),
(
non_ground_fact(ID)
->
format(Handle,'@x~q_*~n~10f~n',[ID,Value]);
format(Handle,'@x~q~n~10f~n',[ID,Value])
),
)
)),
fail; % go to next probabilistic fact
true
),
( % go over all continuous facts
get_continuous_fact_parameters(ID,gaussian(Mu,Sigma)),
format(Handle,'@x~q_*~n0~n0~n~10f;~10f~n',[ID,Mu,Sigma]),
fail; % go to next continuous fact
true
),
forall(get_continuous_fact_parameters(ID,gaussian(Mu,Sigma)),
format(Handle,'@x~q_*~n0~n0~n~10f;~10f~n',[ID,Mu,Sigma])),
close(Handle),
!,
@ -885,11 +772,10 @@ update_query(QueryID,Symbol,What_To_Update) :-
)
),
delete_file(Values_Filename),
delete_file_silently(Values_Filename),
format_learning(4,'~w',[Symbol])
)
),
flush_output(user).
).
%========================================================================
@ -998,51 +884,53 @@ ground_truth_difference :-
%========================================================================
mse_trainingset_only_for_linesearch(MSE) :-
(
current_predicate(user:example/4)
->
(
update_values,
findall(SquaredError,
(user:example(QueryID,_Query,QueryProb,Type),
example_count(Example_Count),
bb_put(error_train_line_search,0.0),
forall(user:example(QueryID,_Query,QueryProb,Type),
(
once(update_query(QueryID,'.',probability)),
query_probability(QueryID,CurrentProb),
once(update_query_cleanup(QueryID)),
(
(Type == '='; (Type == '<', CurrentProb>QueryProb); (Type=='>',CurrentProb<QueryProb))
->
SquaredError is (CurrentProb-QueryProb)**2;
SquaredError = 0.0
(
bb_get(error_train_line_search,Old_Error),
New_Error is Old_Error + (CurrentProb-QueryProb)**2,
bb_put(error_train_line_search,New_Error)
);true
)
)
),
AllSquaredErrors),
length(AllSquaredErrors,Length),
sum_list(AllSquaredErrors,SumAllSquaredErrors),
MSE is SumAllSquaredErrors/Length,
format_learning(3,' (~8f)~n',[MSE])
); true
),
bb_delete(error_train_line_search,Error),
MSE is Error/Example_Count,
format_learning(3,' (~8f)~n',[MSE]),
retractall(values_correct).
mse_testset :-
(
(current_predicate(user:test_example/4),user:test_example(_,_,_,_))
->
(
current_iteration(Iteration),
create_test_predictions_file_name(Iteration,File_Name),
open(File_Name,'write',Handle),
format(Handle,"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%~n",[]),
format(Handle,"% Iteration, train/test, QueryID, Query, GroundTruth, Prediction %~n",[]),
format(Handle,"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%~n",[]),
format_learning(2,'MSE_Test ',[]),
update_values,
bb_put(llh_test_queries,0.0),
findall(SquaredError,
(user:test_example(QueryID,_Query,QueryProb,Type),
(user:test_example(QueryID,Query,TrueQueryProb,Type),
once(update_query(QueryID,'+',probability)),
query_probability(QueryID,CurrentProb),
format(Handle,'ex(~q,test,~q,~q,~10f,~10f).~n',[Iteration,QueryID,Query,TrueQueryProb,CurrentProb]),
once(update_query_cleanup(QueryID)),
(
(Type == '='; (Type == '<', CurrentProb>QueryProb); (Type=='>',CurrentProb<QueryProb))
->
SquaredError is (CurrentProb-QueryProb)**2;
SquaredError is (CurrentProb-TrueQueryProb)**2;
SquaredError = 0.0
),
bb_get(llh_test_queries,Old_LLH_Test_Queries),
@ -1051,20 +939,31 @@ mse_testset :-
),
AllSquaredErrors),
close(Handle),
bb_delete(llh_test_queries,LLH_Test_Queries),
length(AllSquaredErrors,Length),
(
Length>0
->
(
sum_list(AllSquaredErrors,SumAllSquaredErrors),
min_list(AllSquaredErrors,MinError),
max_list(AllSquaredErrors,MaxError),
MSE is SumAllSquaredErrors/Length,
bb_delete(llh_test_queries,LLH_Test_Queries),
MSE is SumAllSquaredErrors/Length
);(
MSE=0.0,
MinError=0.0,
MaxError=0.0
)
),
logger_set_variable(mse_testset,MSE),
logger_set_variable(mse_min_testset,MinError),
logger_set_variable(mse_max_testset,MaxError),
logger_set_variable(llh_test_queries,LLH_Test_Queries),
format_learning(2,' (~8f)~n',[MSE])
); true
).
format_learning(2,' (~8f)~n',[MSE]).
%========================================================================
%= Calculates the sigmoid function respectivly the inverse of it
@ -1097,13 +996,10 @@ inv_sigmoid(T,InvSig) :-
%========================================================================
save_old_probabilities :-
( % go over all tunable facts
tunable_fact(FactID,_),
forall(tunable_fact(FactID,_),
(
continuous_fact(FactID)
->
(
get_continuous_fact_parameters(FactID,gaussian(OldMu,OldSigma)),
atomic_concat(['old_mu_',FactID],Key),
@ -1116,17 +1012,13 @@ save_old_probabilities :-
atomic_concat(['old_prob_',FactID],Key),
bb_put(Key,OldProbability)
)
),
fail; % go to next tunable fact
true
)
).
forget_old_probabilities :-
( % go over all tunable facts
tunable_fact(FactID,_),
forall(tunable_fact(FactID,_),
(
continuous_fact(FactID)
->
@ -1146,15 +1038,11 @@ forget_old_probabilities :-
bb_delete(Key,_),
bb_delete(Key2,_)
)
),
fail; % go to next tunable fact
true
)
).
add_gradient(Learning_Rate) :-
( % go over all tunable facts
tunable_fact(FactID,_),
forall(tunable_fact(FactID,_),
(
continuous_fact(FactID)
->
@ -1189,15 +1077,19 @@ add_gradient(Learning_Rate) :-
Prob_Secure is min(0.999999999,max(0.000000001,NewProbability)),
set_fact_probability(FactID,Prob_Secure)
)
),
fail; % go to next tunable fact
true
)
),
retractall(values_correct).
gradient_descent :-
current_iteration(Iteration),
create_training_predictions_file_name(Iteration,File_Name),
open(File_Name,'write',Handle),
format(Handle,"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%~n",[]),
format(Handle,"% Iteration, train/test, QueryID, Query, GroundTruth, Prediction %~n",[]),
format(Handle,"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%~n",[]),
format_learning(2,'Gradient ',[]),
save_old_probabilities,
@ -1206,9 +1098,7 @@ gradient_descent :-
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% start set gradient to zero
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
( % go over all tunable facts
tunable_fact(FactID,_),
forall(tunable_fact(FactID,_),
(
continuous_fact(FactID)
->
@ -1223,16 +1113,11 @@ gradient_descent :-
atomic_concat(['grad_',FactID],Key),
bb_put(Key,0.0)
)
),
fail; % go to next tunable fact
true
)
),
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% stop gradient to zero
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
!,
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% start calculate gradient
@ -1246,11 +1131,11 @@ gradient_descent :-
logger_set_variable(alpha,Alpha),
example_count(Example_Count),
( % go over all training examples
current_predicate(user:example/4),
user:example(QueryID,_Query,QueryProb,Type),
forall(user:example(QueryID,Query,QueryProb,Type),
(
once(update_query(QueryID,'.',all)),
query_probability(QueryID,BDDProb),
format(Handle,'ex(~q,train,~q,~q,~10f,~10f).~n',[Iteration,QueryID,Query,QueryProb,BDDProb]),
(
QueryProb=:=0.0
->
@ -1293,7 +1178,6 @@ gradient_descent :-
(
continuous_fact(FactID)
->
(
atomic_concat(['grad_mu_',FactID],Key),
atomic_concat(['grad_sigma_',FactID],Key2),
@ -1335,15 +1219,15 @@ gradient_descent :-
true
),
once(update_query_cleanup(QueryID)),
fail; % go to next training example
true
),
once(update_query_cleanup(QueryID))
)),
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% stop calculate gradient
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
!,
close(Handle),
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% start statistics on gradient
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@ -1431,24 +1315,15 @@ lineSearch(Final_X,Final_Value) :-
% init values
Acc is Tol * (B-A),
InitRight is A + Tau*(B-A),
InitLeft is A + B - InitRight,
InitLeft is B - Tau*(B-A),
line_search_evaluate_point(A,Value_A),
line_search_evaluate_point(B,Value_B),
line_search_evaluate_point(InitRight,Value_InitRight),
line_search_evaluate_point(InitLeft,Value_InitLeft),
bb_put(line_search_a,A),
bb_put(line_search_b,B),
bb_put(line_search_left,InitLeft),
bb_put(line_search_right,InitRight),
bb_put(line_search_value_a,Value_A),
bb_put(line_search_value_b,Value_B),
bb_put(line_search_value_left,Value_InitLeft),
bb_put(line_search_value_right,Value_InitRight),
bb_put(line_search_iteration,1),
Parameters=ls(A,B,InitLeft,InitRight,Value_A,Value_B,Value_InitLeft,Value_InitRight,1),
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%% BEGIN BACK TRACKING
@ -1456,16 +1331,7 @@ lineSearch(Final_X,Final_Value) :-
(
repeat,
bb_get(line_search_iteration,Iteration),
bb_get(line_search_a,Ak),
bb_get(line_search_b,Bk),
bb_get(line_search_left,Left),
bb_get(line_search_right,Right),
bb_get(line_search_value_a,Fl),
bb_get(line_search_value_b,Fr),
bb_get(line_search_value_left,FLeft),
bb_get(line_search_value_right,FRight),
Parameters=ls(Ak,Bk,Left,Right,Fl,Fr,FLeft,FRight,Iteration),
(
% check for infinity, if there is, go to the left
@ -1476,40 +1342,40 @@ lineSearch(Final_X,Final_Value) :-
FlNew=FLeft,
LeftNew=Right,
FLeftNew=FRight,
RightNew is AkNew + Bk - LeftNew,
RightNew is Left + Bk - Right,
line_search_evaluate_point(RightNew,FRightNew),
BkNew=Bk,
FrNew=Fr
FrNew=Fr,
Interval_Size is Bk-Left
);
(
BkNew=Right,
FrNew=FRight,
RightNew=Left,
FRightNew=FLeft,
LeftNew is Ak + BkNew - RightNew,
LeftNew is Ak + Right - Left,
line_search_evaluate_point(LeftNew,FLeftNew),
AkNew=Ak,
FlNew=Fl
FlNew=Fl,
Interval_Size is Right-Ak
)
),
Next_Iteration is Iteration + 1,
bb_put(line_search_iteration,Next_Iteration),
bb_put(line_search_a,AkNew),
bb_put(line_search_b,BkNew),
bb_put(line_search_left,LeftNew),
bb_put(line_search_right,RightNew),
bb_put(line_search_value_a,FlNew),
bb_put(line_search_value_b,FrNew),
bb_put(line_search_value_left,FLeftNew),
bb_put(line_search_value_right,FRightNew),
nb_setarg(9,Parameters,Next_Iteration),
nb_setarg(1,Parameters,AkNew),
nb_setarg(2,Parameters,BkNew),
nb_setarg(3,Parameters,LeftNew),
nb_setarg(4,Parameters,RightNew),
nb_setarg(5,Parameters,FlNew),
nb_setarg(6,Parameters,FrNew),
nb_setarg(7,Parameters,FLeftNew),
nb_setarg(8,Parameters,FRightNew),
% is the search interval smaller than the tolerance level?
BkNew-AkNew<Acc,
Interval_Size<Acc,
% apperantly it is, so get me out of here and
% cut away the choice point from repeat
@ -1519,16 +1385,7 @@ lineSearch(Final_X,Final_Value) :-
%%%% END BACK TRACKING
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% clean up the blackboard mess
bb_delete(line_search_iteration,_),
bb_delete(line_search_a,_),
bb_delete(line_search_b,_),
bb_delete(line_search_left,_),
bb_delete(line_search_right,_),
bb_delete(line_search_value_a,_),
bb_delete(line_search_value_b,_),
bb_delete(line_search_value_left,_),
bb_delete(line_search_value_right,_),
% it doesn't harm to check also the value in the middle
% of the current search interval
@ -1611,36 +1468,6 @@ my_5_min(V1,V2,V3,V4,V5,F1,F2,F3,F4,F5,VMin,FMin) :-
).
%========================================================================
%= set the alpha parameter to the value
%= # positive training examples / # negative training examples
%=
%= training example is positive if P(e)=1
%= training example is negative if P(e)=0
%=
%= if there are training example with 0<P<1, set alpha=1.0
%========================================================================
auto_alpha :-
\+ current_predicate(user:example/4),
!,
set_problog_flag(alpha,1.0).
auto_alpha :-
user:example(_,_,P,_),
P<1,
P>0,
!,
set_problog_flag(alpha,1.0).
auto_alpha :-
findall(1,(user:example(_,_,P,=),P=:=1.0),Pos),
findall(0,(user:example(_,_,P,=),P=:=0.0),Neg),
length(Pos,NP),
length(Neg,NN),
Alpha is NP/NN,
set_problog_flag(alpha,Alpha).
%========================================================================
%= initialize the logger module and set the flags for learning