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Problog

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This commit is contained in:
Vítor Santos Costa 2018-08-31 20:03:00 +01:00
parent e0cc401381
commit f6d8304fcf
9 changed files with 103 additions and 98 deletions
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11
library/lists.yap
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@ -358,17 +358,6 @@ remove_duplicates([Elem|L], [Elem|NL]) :-
delete(L, Elem, Temp), delete(L, Elem, Temp),
remove_duplicates(Temp, NL). remove_duplicates(Temp, NL).
% reverse(List, Reversed)
% is true when List and Reversed are lists with the same elements
% but in opposite orders. rev/2 is a synonym for reverse/2.
reverse(List, Reversed) :-
reverse(List, [], Reversed).
reverse([], Reversed, Reversed).
reverse([Head|Tail], Sofar, Reversed) :-
reverse(Tail, [Head|Sofar], Reversed).
% same_length(?List1, ?List2) % same_length(?List1, ?List2)
% is true when List1 and List2 are both lists and have the same number % is true when List1 and List2 are both lists and have the same number

14
library/tries/base_tries.h
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@ -135,13 +135,13 @@ void trie_max_stats(YAP_Int *memory, YAP_Int *tries, YAP_Int *entries, YAP_I
void trie_usage(TrEntry trie, YAP_Int *entries, YAP_Int *nodes, YAP_Int *virtual_nodes); void trie_usage(TrEntry trie, YAP_Int *entries, YAP_Int *nodes, YAP_Int *virtual_nodes);
void trie_print(TrEntry trie); void trie_print(TrEntry trie);
void trie_data_construct(TrNode node); extern void trie_data_construct(TrNode node);
void trie_set_traverse_mode(YAP_Int mode); extern void trie_set_traverse_mode(YAP_Int mode);
YAP_Int trie_get_traverse_mode(void); extern YAP_Int trie_get_traverse_mode(void);
TrData trie_traverse_first(TrEntry trie); extern TrData trie_traverse_first(TrEntry trie);
TrData trie_traverse_next(TrData data); extern TrData trie_traverse_next(TrData data);
void trie_disable_hash_table(void); extern void trie_disable_hash_table(void);
void trie_enable_hash_table(void); extern void trie_enable_hash_table(void);
YAP_Term trie_to_list(TrEntry trie); YAP_Term trie_to_list(TrEntry trie);

50
library/tries/core_tries.h
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@ -287,32 +287,32 @@ typedef struct trie_hash {
/* API */ /* API */
/* --------------------------- */ /* --------------------------- */
TrEngine core_trie_init_module(void); extern TrEngine core_trie_init_module(void);
TrNode core_trie_open(TrEngine engine); extern TrNode core_trie_open(TrEngine engine);
void core_trie_close(TrEngine engine, TrNode node, void (*destruct_function)(TrNode)); extern void core_trie_close(TrEngine engine, TrNode node, void (*destruct_function)(TrNode));
void core_trie_close_all(TrEngine engine, void (*destruct_function)(TrNode)); extern void core_trie_close_all(TrEngine engine, void (*destruct_function)(TrNode));
void core_trie_set_mode(YAP_Int mode); extern void core_trie_set_mode(YAP_Int mode);
YAP_Int core_trie_get_mode(void); extern YAP_Int core_trie_get_mode(void);
TrNode core_trie_put_entry(TrEngine engine, TrNode node, YAP_Term entry, YAP_Int *depth); extern TrNode core_trie_put_entry(TrEngine engine, TrNode node, YAP_Term entry, YAP_Int *depth);
TrNode core_trie_check_entry(TrNode node, YAP_Term entry); extern TrNode core_trie_check_entry(TrNode node, YAP_Term entry);
YAP_Term core_trie_get_entry(TrNode node); extern YAP_Term core_trie_get_entry(TrNode node);
void core_trie_remove_entry(TrEngine engine, TrNode node, void (*destruct_function)(TrNode)); extern void core_trie_remove_entry(TrEngine engine, TrNode node, void (*destruct_function)(TrNode));
void core_trie_remove_subtree(TrEngine engine, TrNode node, void (*destruct_function)(TrNode)); extern void core_trie_remove_subtree(TrEngine engine, TrNode node, void (*destruct_function)(TrNode));
void core_trie_add(TrNode node_dest, TrNode node_source, void (*add_function)(TrNode, TrNode)); extern void core_trie_add(TrNode node_dest, TrNode node_source, void (*add_function)(TrNode, TrNode));
void core_trie_join(TrEngine engine, TrNode node_dest, TrNode node_source, void (*add_function)(TrNode, TrNode), void (*copy_function)(TrNode, TrNode)); extern void core_trie_join(TrEngine engine, TrNode node_dest, TrNode node_source, void (*add_function)(TrNode, TrNode), void (*copy_function)(TrNode, TrNode));
void core_trie_intersect(TrEngine engine, TrNode node_dest, TrNode node_source, void (*add_function)(TrNode, TrNode), void (*destruct_function)(TrNode)); extern void core_trie_intersect(TrEngine engine, TrNode node_dest, TrNode node_source, void (*add_function)(TrNode, TrNode), void (*destruct_function)(TrNode));
YAP_Int core_trie_count_join(TrNode node1, TrNode node2); extern YAP_Int core_trie_count_join(TrNode node1, TrNode node2);
YAP_Int core_trie_count_intersect(TrNode node1, TrNode node2); extern YAP_Int core_trie_count_intersect(TrNode node1, TrNode node2);
void core_trie_save(TrNode node, FILE *file, void (*save_function)(TrNode, FILE *)); extern void core_trie_save(TrNode node, FILE *file, void (*save_function)(TrNode, FILE *));
TrNode core_trie_load(TrEngine engine, FILE *file, void (*load_function)(TrNode, YAP_Int, FILE *)); extern TrNode core_trie_load(TrEngine engine, FILE *file, void (*load_function)(TrNode, YAP_Int, FILE *));
void core_trie_stats(TrEngine engine, YAP_Int *memory, YAP_Int *tries, YAP_Int *entries, YAP_Int *nodes); extern void core_trie_stats(TrEngine engine, YAP_Int *memory, YAP_Int *tries, YAP_Int *entries, YAP_Int *nodes);
void core_trie_max_stats(TrEngine engine, YAP_Int *memory, YAP_Int *tries, YAP_Int *entries, YAP_Int *nodes); extern void core_trie_max_stats(TrEngine engine, YAP_Int *memory, YAP_Int *tries, YAP_Int *entries, YAP_Int *nodes);
void core_trie_usage(TrNode node, YAP_Int *entries, YAP_Int *nodes, YAP_Int *virtual_nodes); extern void core_trie_usage(TrNode node, YAP_Int *entries, YAP_Int *nodes, YAP_Int *virtual_nodes);
void core_trie_print(TrNode node, void (*print_function)(TrNode)); extern void core_trie_print(TrNode node, void (*print_function)(TrNode));
void core_disable_hash_table(void); extern void core_disable_hash_table(void);
void core_enable_hash_table(void); extern void core_enable_hash_table(void);
YAP_Term core_trie_to_list(TrNode node); extern YAP_Term core_trie_to_list(TrNode node);
#include "core_dbtries.h" #include "core_dbtries.h"

2
packages/ProbLog/problog/logger.yap
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@ -244,7 +244,7 @@ logger_define_variable(Name,Type) :-
-> ->
write('redefining logger variable '),write(Name),write(' of type '), write(Type0), nl write('redefining logger variable '),write(Name),write(' of type '), write(Type0), nl
; ;
throw(error(variable_redefined(logger_define_variable(Name,Type))) throw(error(variable_redefined(logger_define_variable(Name,Type))))
). ).
logger_define_variable(Name,Type) :- logger_define_variable(Name,Type) :-
ground(Type), ground(Type),

2
packages/ProbLog/problog/ptree.yap
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@ -263,7 +263,7 @@
% this is a test to determine whether YAP provides the needed trie library % this is a test to determine whether YAP provides the needed trie library
:- initialization( :- initialization(
( predicate_property(trie_disable_hash, imported_from(tries)) -> ( predicate_property(trie_disable_hash, imported_from(M)) ->
trie_disable_hash trie_disable_hash
; print_message(warning,'The predicate tries:trie_disable_hash/0 does not exist. Please update trie library.') ; print_message(warning,'The predicate tries:trie_disable_hash/0 does not exist. Please update trie library.')
) )

101
packages/ProbLog/problog_learning_lbdd.yap
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@ -389,8 +389,6 @@ reset_learning :-
do_learning(Iterations) :- do_learning(Iterations) :-
do_learning(Iterations,-1). do_learning(Iterations,-1).
:- spy do_learning/2.
do_learning(Iterations,Epsilon) :- do_learning(Iterations,Epsilon) :-
current_predicate(user:example/4), current_predicate(user:example/4),
!, !,
@ -514,32 +512,7 @@ init_learning :-
% if yes, switch to problog_exact % if yes, switch to problog_exact
% continuous facts are not supported yet. % continuous facts are not supported yet.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
problog_flag(continuous_facts, true), set_default_gradient_method,
!,
problog_flag(init_method,(_,_,_,_,OldCall)),
(
(
continuous_fact(_),
OldCall\=problog_exact_save(_,_,_,_,_)
)
->
(
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
),
succeeds_n_times(user:test_example(_,_,_,_),TestExampleCount), succeeds_n_times(user:test_example(_,_,_,_),TestExampleCount),
format_learning(3,'~q test examples~n',[TestExampleCount]), format_learning(3,'~q test examples~n',[TestExampleCount]),
@ -597,6 +570,21 @@ init_learning :-
empty_bdd_directory. empty_bdd_directory.
set_default_gradient_method :-
problog_flag(continuous_facts, true),
!,
problog_flag(init_method,OldMethod),
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))).
set_default_gradient_method :-
problog_tabled(_), problog_flag(fast_proofs,false),
!,
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))).
set_default_gradient_method :-
set_problog_flag(init_method,(Query,1,BDD,
problog_kbest_as_bdd(user:Query,1,BDD))).
%======================================================================== %========================================================================
%= This predicate goes over all training and test examples, %= This predicate goes over all training and test examples,
%= calls the inference method of ProbLog and stores the resulting %= calls the inference method of ProbLog and stores the resulting
@ -625,29 +613,23 @@ init_one_query(QueryID,Query,Type) :-
format_learning(3,' Reuse existing BDD ~q~n~n',[QueryID]); format_learning(3,' Reuse existing BDD ~q~n~n',[QueryID]);
( (
b_setval(problog_required_keep_ground_ids,false), b_setval(problog_required_keep_ground_ids,false),
problog_flag(libbdd_init_method,(Query,Bdd,Call)), rb_new(H0),
problog_flag(init_method,(Query,NOf,Bdd,problog_kbest_as_bdd(Call,1,Bdd))),
strip_module(Call,_,gene(X,Y)),
!,
Bdd = bdd(Dir, Tree, MapList), Bdd = bdd(Dir, Tree, MapList),
% trace, % trace,
once(Call), problog:problog_kbest_as_bdd(user:gene(X,Y),1,Bdd),
rb_new(H0),
maplist_to_hash(MapList, H0, Hash), maplist_to_hash(MapList, H0, Hash),
Tree \= [], Tree \= [],
%put_code(0'.),
writeln(QueryID), writeln(QueryID),
tree_to_grad(Tree, Hash, [], Grad), tree_to_grad(Tree, Hash, [], Grad),
recordz(QueryID,bdd(Dir, Grad, MapList),_) recordz(QueryID,bdd(Dir, Grad, MapList),_)
) )
), ).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% init_one_query(_QueryID,_Query,_Type) :-
% check wether this BDD is similar to another BDD throw(unsupported_init_method).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
(
problog_flag(check_duplicate_bdds,true)
->
true /* ignore this flag for now */
;
true
),!.
init_one_query(_QueryID,_Query,_Type).
@ -1006,6 +988,7 @@ inv_sigmoid(T,InvSig) :-
save_old_probabilities :- save_old_probabilities :-
problog_flag(continous_facts, true), problog_flag(continous_facts, true),
!,
forall(tunable_fact(FactID,_), forall(tunable_fact(FactID,_),
( (
continuous_fact(FactID) continuous_fact(FactID)
@ -1024,6 +1007,14 @@ save_old_probabilities :-
) )
) )
). ).
save_old_probabilities :-
forall(tunable_fact(FactID,_),
(
get_fact_probability(FactID,OldProbability),
atomic_concat(['old_prob_',FactID],Key),
bb_put(Key,OldProbability)
)
).
@ -1106,7 +1097,8 @@ gradient_descent :-
save_old_probabilities, save_old_probabilities,
update_values, update_values,
reset_gradients. reset_gradients,
compute_gradients(Handle).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% start set gradient to zero % start set gradient to zero
@ -1130,7 +1122,14 @@ gradient_descent :-
bb_put(Key,0.0) bb_put(Key,0.0)
) )
) )
), ).
reset_gradients :-
forall(tunable_fact(FactID,_),
(
atomic_concat(['grad_',FactID],Key),
bb_put(Key,0.0)
)
).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% stop gradient to zero % stop gradient to zero
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@ -1138,6 +1137,7 @@ gradient_descent :-
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% start calculate gradient % start calculate gradient
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
compute_gradients(Handle) :-
bb_put(mse_train_sum, 0.0), bb_put(mse_train_sum, 0.0),
bb_put(mse_train_min, 0.0), bb_put(mse_train_min, 0.0),
bb_put(mse_train_max, 0.0), bb_put(mse_train_max, 0.0),
@ -1485,18 +1485,18 @@ my_5_min(V1,V2,V3,V4,V5,F1,F2,F3,F4,F5,VMin,FMin) :-
%======================================================================== %========================================================================
init_flags :- init_flags :-
prolog_file_name('queries',Queries_Folder), % get absolute file name for './queries' prolog_file_name(queries,Queries_Folder), % get absolute file name for './queries'
prolog_file_name('output',Output_Folder), % get absolute file name for './output' prolog_file_name(output,Output_Folder), % get absolute file name for './output'
problog_define_flag(bdd_directory, problog_flag_validate_directory, 'directory for BDD scripts', Queries_Folder,learning_general), problog_define_flag(bdd_directory, problog_flag_validate_directory, 'directory for BDD scripts', Queries_Folder,learning_general),
problog_define_flag(output_directory, problog_flag_validate_directory, 'directory for logfiles etc', Output_Folder,learning_general,flags:learning_output_dir_handler), problog_define_flag(output_directory, problog_flag_validate_directory, 'directory for logfiles etc', Output_Folder,learning_general,flags:learning_output_dir_handler),
problog_define_flag(log_frequency, problog_flag_validate_posint, 'log results every nth iteration', 1, learning_general), problog_define_flag(log_frequency, problog_flag_validate_posint, 'log results every nth iteration', 1, learning_general),
problog_define_flag(rebuild_bdds, problog_flag_validate_nonegint, 'rebuild BDDs every nth iteration', 0, learning_general), problog_define_flag(rebuild_bdds, problog_flag_validate_nonegint, 'rebuild BDDs every nth iteration', 0, learning_general),
problog_define_flag(reuse_initialized_bdds,problog_flag_validate_boolean, 'Reuse BDDs from previous runs',false, learning_general), problog_define_flag(reuse_initialized_bdds,problog_flag_validate_boolean, 'Reuse BDDs from previous runs',false, learning_general),
problog_define_flag(check_duplicate_bdds,problog_flag_validate_boolean,'Store intermediate results in hash table',true,learning_general), problog_define_flag(check_duplicate_bdds,problog_flag_validate_boolean,'Store intermediate results in hash table',true,learning_general),
problog_define_flag(libbdd_init_method,problog_flag_validate_dummy,'ProbLog predicate to search proofs',(Query,Tree,problog:problog_kbest_as_bdd(Query,100,Tree)),learning_general,flags:learning_libdd_init_handler), problog_define_flag(init_method,problog_flag_validate_dummy,'ProbLog predicate to search proofs',(Query,Tree,problog:problog_kbest_as_bdd(Query,100,Tree)),learning_general,flags:learning_libdd_init_handler),
problog_define_flag(alpha,problog_flag_validate_number,'weight of negative examples (auto=n_p/n_n)',auto,learning_general,flags:auto_handler), problog_define_flag(alpha,problog_flag_validate_number,'weight of negative examples (auto=n_p/n_n)',auto,learning_general,flags:auto_handler),
problog_define_flag(sigmoid_slope,problog_flag_validate_posnumber,'slope of sigmoid function',1.0,learning_general), problog_define_flag(sigmoid_slope,problog_flag_validate_posnumber,'slope of sigmoid function',1.0,learning_general),
problog_define_flag(continuous_facts,problog_flag_validate_boolean,'support parameter learning of continuous distributions',1.0,learning_general), problog_define_flag(continuous_facts,problog_flag_validate_boolean,'support parameter learning of continuous distributions',true,learning_general),
problog_define_flag(learning_rate,problog_flag_validate_posnumber,'Default learning rate (If line_search=false)',examples,learning_line_search,flags:examples_handler), problog_define_flag(learning_rate,problog_flag_validate_posnumber,'Default learning rate (If line_search=false)',examples,learning_line_search,flags:examples_handler),
problog_define_flag(line_search, problog_flag_validate_boolean,'estimate learning rate by line search',false,learning_line_search), problog_define_flag(line_search, problog_flag_validate_boolean,'estimate learning rate by line search',false,learning_line_search),
@ -1505,7 +1505,6 @@ init_flags :-
problog_define_flag(line_search_tolerance,problog_flag_validate_posnumber,'tolerance value for line search',0.05,learning_line_search), problog_define_flag(line_search_tolerance,problog_flag_validate_posnumber,'tolerance value for line search',0.05,learning_line_search),
problog_define_flag(line_search_interval, problog_flag_validate_dummy,'interval for line search',(0,100),learning_line_search,flags:linesearch_interval_handler). problog_define_flag(line_search_interval, problog_flag_validate_dummy,'interval for line search',(0,100),learning_line_search,flags:linesearch_interval_handler).
init_logger :- init_logger :-
logger_define_variable(iteration, int), logger_define_variable(iteration, int),
logger_define_variable(duration,time), logger_define_variable(duration,time),
@ -1527,5 +1526,7 @@ init_logger :-
logger_define_variable(llh_test_queries,float). logger_define_variable(llh_test_queries,float).
:- initialization(init_flags). :- initialization(init_flags).
:- initialization(init_logger). :- initialization(init_logger).

11
pl/bootlists.yap
View File

@ -136,3 +136,14 @@ prolog:length(L, M) :-
%% @} %% @}
% reverse(List, Reversed)
% is true when List and Reversed are lists with the same elements
% but in opposite orders. rev/2 is a synonym for reverse/2.
lists:reverse(List, Reversed) :-
lists:reverse(List, [], Reversed).
lists:reverse([], Reversed, Reversed).
lists:reversae([Head|Tail], Sofar, Reversed) :-
lists:reverse(Tail, [Head|Sofar], Reversed).

8
pl/consult.yap
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@ -855,7 +855,10 @@ nb_setval('$if_le1vel',0).
'__NB_getval__'('$lf_status', TOpts, fail), '__NB_getval__'('$lf_status', TOpts, fail),
'$lf_opt'( initialization, TOpts, Ref), '$lf_opt'( initialization, TOpts, Ref),
nb:nb_queue_close(Ref, Answers, []), nb:nb_queue_close(Ref, Answers, []),
lists:member(G, Answers), '$process_init_goal'(Answers).
'$exec_initialization_goals'.
'$process_init_goal'([G|_]) :-
'$yap_strip_module'( G, M0, G0), '$yap_strip_module'( G, M0, G0),
( (
catch(M0:G0, Error, user:'$LoopError'(Error, top)) catch(M0:G0, Error, user:'$LoopError'(Error, top))
@ -865,7 +868,8 @@ nb_setval('$if_le1vel',0).
format(user_error,':- ~w:~w failed.~n',[M0,G0]) format(user_error,':- ~w:~w failed.~n',[M0,G0])
), ),
fail. fail.
'$exec_initialization_goals'. '$process_init_goal'([_|Gs]) :-
'$process_init_goal'(Gs).
/** /**
@pred include(+ _F_) is directive @pred include(+ _F_) is directive

2
pl/preds.yap
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@ -535,7 +535,7 @@ predicate_property(Pred,Prop) :-
functor(P,N,A), functor(P,N,A),
once(recorded('$module','$module'(_TFN,M,_S,Publics,_L),_)), once(recorded('$module','$module'(_TFN,M,_S,Publics,_L),_)),
lists:memberchk(N/A,Publics). lists:memberchk(N/A,Publics).
'$predicate_property'(P,M,M0,imported_from(M0)) :- '$predicate_property'(P,M,M0,imported_from(M)) :-
M \= M0. M \= M0.
'$predicate_property'(P,Mod,_,number_of_clauses(NCl)) :- '$predicate_property'(P,Mod,_,number_of_clauses(NCl)) :-
'$number_of_clauses'(P,Mod,NCl). '$number_of_clauses'(P,Mod,NCl).