diogo/yap-6.3
Archived
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

MLN stuff

Browse Source
This commit is contained in:
Vitor Santos Costa 2013-06-19 21:38:43 -05:00
parent 24714dbd01
commit cc73f426d9
3 changed files with 364 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

283
packages/CLPBN/learning/learn_mln_wgts.yap Normal file
View File

@ -0,0 +1,283 @@
%
% generative learning in MLNs:
%
% maximise SUM log Pw(Xi=xi|mb(Xi))
%
% or sum N(X) - p(0|mb)n0 - P(1|mb)n1
%
% note that Pw(X|MB) = P(0|MB) || P(1|MB)
%
%
:- use_module(library(lists)).
:- use_module(library(maplist)).
:- use_module(library(nb)).
:- use_module(library(mlns)).
:- use_module(library(pfl)).
:- use_module(library(lbfgs)).
:- dynamic diff/4, i/2.
prior_means(_, 0.0).
prior_dev(_, 100.0).
learn_mln_generative :-
compile,
optimize.
set_weights :-
retract( mln:mln_w(Id, _) ),
optimizer_get_x( Id, W),
% writeln(weight:W),
assert( mln:mln_w(Id, W) ),
fail.
set_weights.
add_lprior(Id-WI, Lik0, Lik) :-
prior_means(Id, PM),
prior_dev(Id, PV),
Lik is Lik0 + ((WI-PM)*(WI-PM))/(2*PV*PV).
adjust_lprior(Lik0, Lik) :-
Lik0 = Lik, !.
adjust_lprior(Lik0, Lik) :-
findall(I-WI, mln_w(I,WI), WIs),
foldl(add_lprior, WIs, Lik0, Lik).
likelihood(Lik) :-
S = s(0.0),
% nb_create_accumulator(0.0, Acc),
(
lmln:p(_Lit,P,_,_),
LogP is log(P),
% writeln(_Lit:P),
S = s(V),
V1 is V+LogP,
nb_setarg(1, S, V1),
% nb_add_to_accumulator( Acc, LogP),
fail
;
% nb_accumulator_value(Acc, Lik)
S = s(Lik0),
writeln(lik:Lik0),
adjust_lprior(Lik0, Lik1),
Lik is -Lik1
).
adjust_prior(Lik0, _, Lik) :-
Lik0 = Lik, !.
adjust_prior(Sum, Id, NSum) :-
mln_w(Id, Wi),
prior_means(Id, PM),
prior_dev(Id, PV),
NSum is Sum+(Wi-PM)/(PV*PV).
derive :-
mln(Id, _, Els, _),
i(Id, N),
%writeln(Id:N),
% nb_create_accumulator(0.0, Acc),
S = s(0.0),
% nb_accumulator_value(Acc, Sum0),writeln(sum0:Sum0),
(
nth(_L, Els, VId),
p_l(Id, VId, P0, P1),
diff( VId, Id, DN0, DN1),
X is (N-P0*(N+DN0)-P1*(N+DN1)),
%writeln(X is (N-P0*(N+DN0)-P1*(N+DN1))),
% nb_add_to_accumulator(Acc, X),
S = s(V),
V1 is V-X,
nb_setarg(1, S, V1),
fail
;
% nb_accumulator_value(Acc, Sum),
S = s(Sum),
writeln(d:Id:Sum),
adjust_prior(Sum, Id, NSum),
optimizer_set_g(Id, NSum ),
fail
).
derive.
% This is the call back function which is invoked to report the progress
% if the last argument is set to anywhting else than 0, the optimizer will
% stop right now
progress(FX,X_Norm,G_Norm,Step,_N,Iteration,Ls,0) :-
optimizer_get_x(0,X0),
format('~d. Iteration : w=~4f f(X)=~4f |X|=~4f |X\'|=~4f Step=~4f Ls=~4f~n',[Iteration,X0,FX,X_Norm,G_Norm,Step,Ls]).
% This is the call back function which evaluates F and the gradient of F
evaluate(FX,_N,_Step) :-
set_weights,
likelihood(FX),
derive.
init_vars(Ev, Pr) :-
mln(N),
N1 is N-1,
format('We start the search at weight=0~2n',[]),
optimizer_initialize(N, Ev, Pr),
between(0, N1, I),
optimizer_set_x(I,0.0),
fail.
init_vars(_, _).
output_stat(BestF, Status) :-
mln(N),
N1 is N-1,
( between(0,N1,I),
optimizer_get_x(I,BestX0),
format('w[~d] = ~f~n', [I, BestX0]),
fail
;
Lik is -BestF,
format('Final likelihood=~f~2nLBFGS Status=~w~n',[Lik,Status])
).
optimize :-
init_vars(evaluate, progress),
optimizer_run(BestF,Status),
output_stat(BestF, Status),
optimizer_finalize,
format('~2nOptimization done~n',[]).
compile :-
init_compiler,
mln(ParFactor, _Type, _Els, _G),
factor(markov, ParFactor, Ks, _, _Phi, Constraints),
maplist(call, Constraints),
nth(_L, Ks, VId),
compile_pw(VId, P0, P1, G),
assert((p_l(ParFactor, VId, P0, P1) :- lmln:G)),
fail.
compile.
init_compiler :-
retractall(i(_,_)),
retractall(i(_,_,_,_)),
retractall(p_l(_,_,_,_)),
retractall(lmln:p(_,_,_,_)),
fail.
init_compiler.
compile_pw(VId, P0, P1, p(VId, _, P0, P1)) :-
clause(lmln:p(VId, _, P0, P1), _), !.
compile_pw(VId, Head0, Head1, G) :-
G = p(VId, Head, Head0, Head1),
compile(VId,Head,Head0,Head1,Bd),
assert( ( lmln:G :- Bd) ).
compile(VId, P, P0, P1, Bd) :-
findall(p(FId,W,P0,P1), find_prob(VId, FId, W, P0, P1), Fs),
(evidence(VId, 1) -> P = P1 ; P = P0),
(
Fs == [] -> fail
;
Fs = [p(F,W,1,1)]
->
P0 = 0.5, P1 = 0.5, Bd = true
; Fs = [p(F,W,P0A,P1A)]
->
Bd = (mln_w(F, W), P0 is P0A/(P0A+P1A), P1 is 1-P0)
;
Fs = [p(FA,WA,P0A,P1A),p(FB,WB,P0B,P1B)]
->
Bd = (mln_w(FA, WA), mln_w(FB, WB), P0 is P0A*P0B/(P0A*P0B+P1A*P1B), P1 is 1-P0)
;
Bd = ( sumps(Fs, V0, 1.0, V1, 1.0), P0 is V1/(V0+V1), P1 is 1-P0)
).
find_prob(VId, ParFactor, W, P0, P1) :-
defined_in_factor(VId, ParFactor, L),
factor(markov, ParFactor, Ks, _, _Phi, Constraints),
nth0(L, Ks, VId),
maplist(call,Constraints),
mln(ParFactor, _Type, LP, _Head),
foldl(true_literal, LP, Ks, 0, NTs),
NTs < 2, % >= 2 ignore, always true...
maplist(polarity(VId, Pol), LP),
(NTs == 0 ->
/* We have no true literal */
( Pol == (+) ->
% inc_n(ParFactor, L1, 1),
(evidence(VId, 1) -> /* we are */
assert(diff(VId,ParFactor,-1, 0))
;
assert(diff(VId, ParFactor, 0, 1))
),
P0 = 1, P1 = exp(W)
;
% inc_n(ParFactor, L1, 0),
(evidence(VId, 1) -> /* we are */
assert(diff(VId,ParFactor, 1, 0))
;
assert(diff(VId, ParFactor, 0, -1))
),
P0 = exp(W), P1 = 1
)
;
/* L == 0: increment true literals once */
(L == 0 -> inc(ParFactor) ; true ),
/* We have a single true literal */
( %are we that literal ?
Pol == (+) ->
(evidence(VId, 1) -> /* we are */
% inc_n(ParFactor, L1, 1),
assert(diff(VId,ParFactor, -1, 0)),
P0 = 1, P1 = exp(W) ;
/* we are not */
assert(diff(VId,ParFactor, 0, 0)),
% inc_n(ParFactor, L1, 0),
% inc_n(ParFactor, L1, 1),
P0 = 1, P1 = 1
)
;
% NEGATIVE polarity
(evidence(VId, 1) -> /* we are not */
assert(diff(VId,ParFactor, 0, 0)),
% inc_n(ParFactor, L1, 0),
% inc_n(ParFactor, L1, 1),
P0 = 1, P1 = 1 ;
/* we are */
assert(diff(VId,ParFactor, 0, -1)),
% inc_n(ParFactor, L1, 0),
P0 = exp(W), P1 = 1
)
)
).
polarity(L, -, -L) :- !.
polarity(L, +, L) :- !.
polarity(_, _, _).
true_literal(-L, L, N, N1) :- !,
( evidence(L, 1) -> N1 = N ; N1 is N+1 ).
true_literal(L, L, N, N1) :-
( evidence(L, 1) -> N1 is N+1 ; N1 = N ).
inc(Id) :-
retract(i(Id, N)), !,
N1 is N+1,
assert(i(Id, N1)).
inc(Id) :-
assert(i(Id, 1)).
% V is f (0)
check(W, V, -V, exp(W), _R, Matters, Matters0) :- !, Matters = Matters0.
check(_W, V, V, R, R, Matters, Matters0) :- !, Matters = Matters0.
check(W, _V, -V, Rf, R0, Matters, Matters0) :- !,
(evidence(V, 1) -> Rf = R0, Matters=Matters0; Rf = exp(W), Matters = not).
check(W, _V, V, Rf, R0, Matters, Matters0) :-
(evidence(V, 1) -> Rf = exp(W), Matters = not ; Rf = R0, Matters=Matters0).
complement(W, exp(W), 1).
complement(W, 1, exp(W)).

71
packages/CLPBN/mlns.yap
View File

@ -1,20 +1,22 @@
:- module(mln,
[op(1150,fx,mln),
op(1150,fx,mln_domain),
mln_domain/1]).
mln_domain/1,
mln/1,
mln/4,
mln_w/2]).
:- use_module(library(pfl)).
:- use_module(library(maplist)).
:- use_module(library(lists)).
:- dynamic mln/1, mln/2, mln_domain/4.
:- dynamic mln/1, mln/2, mln_domain/4, mln/4, mln_w/2.
user:term_expansion(mln_domain(P),[]) :-
expand_domain(P).
user:term_expansion( mln(W: D), pfl:factor(markov,Id,FList,FV,Phi,Constraints)) :-
translate_to_factor(W, D, FList, Id, FV, Phi, Constraints),
writeln(factor(markov,Id,FList,FV,Phi,Constraints)).
translate_to_factor(W, D, FList, Id, FV, Phi, Constraints).
expand_domain((P1,P2)) :- !,
expand_domain(P1),
@ -34,14 +36,17 @@ do_type(NP, Type, I0, I) :-
translate_to_factor(W, D, Lits, Id, Vs, Phi, Domain) :-
W0 is exp(W),
(
Do = disj,
disj_to_list(D, LP, [], Lits, [])
->
findall(F, weight(LP, W0, 1, F), Phi)
;
Do = conj,
conj_to_list(D, LP, [], Lits, [])
->
findall(F, weight(LP, 1, W0, F), Phi)
;
Do = disj,
cnf(D, Fs0, []),
clean_cnf(Fs0, Fs)
->
@ -52,11 +57,46 @@ translate_to_factor(W, D, Lits, Id, Vs, Phi, Domain) :-
new_mln(Id),
maplist(new_skolem(Id), Lits),
term_variables(Lits, Vs),
create_domain(Lits, Domain).
create_domain(Lits, Domain),
make_clause(Id, Do, Vs, Domain, Lits, LP, Head),
assert(mln_w(Id, W)),
assert(mln(Id, Do, LP, Head)).
%
% naive translation of conj/disjunction into Prolog
%
make_clause(Id, Do, Vs, Domain, _Lits, Fs, Head) :-
Head =.. [mln,Id|Vs],
order_body(Do, Fs, Bd0),
add_domain(Domain, Bd, once(Bd0)),
assert_static(user:(Head :- Bd)).
order_body(disj, Fs, Bd0) :-
order_body(Fs, Bd0).
order_body(conj, Fs, Bd0) :-
andder_body(Fs, Bd0),
order_body([-G], (\+ G)).
order_body([G], (G)).
order_body([-G|Gs], (\+G ; NGs)) :-
order_body(Gs, NGs).
order_body([G|Gs], (G ; NGs)) :-
order_body(Gs, NGs).
ander_body([-G], (\+ G)).
ander_body([G], (G)).
ander_body([-G|Gs], (\+G , NGs)) :-
ander_body(Gs, NGs).
ander_body([G|Gs], (G , NGs)) :-
ander_body(Gs, NGs).
add_domain([G], (G,B0), B0) :- !.
add_domain([G|Gs], (G,NGs), G0) :-
add_domain(Gs, NGs, G0).
new_skolem(Id, Lit) :-
pfl:new_skolem(Lit, [t,f]),
pfl:new_skolem(Lit, [f,t]),
assert(pfl:skolem_in(Lit, Id)).
mln(0).
@ -148,7 +188,9 @@ create_dgoal(I0, Arity, Lit) -->
[ TypeG ],
create_dgoal(I, Arity, Lit).
%
% very simple, inneficient converter from logic expressions to cnf
%
cnf(V) --> { var(V) }, !,
[[V]].
cnf((A->B)) --> !,
@ -210,3 +252,18 @@ clean_cnf(CNF, NCNF) :-
maplist(sort, CNF, CNF1),
sort(CNF1, NCNF).
%
% count groundings
%
all_true(Id, V) :-
mln(Id, _F, _D, Head),
nb_create_accumulator(0, Acc),
(
call(user:Head),
nb_add_to_accumulator(Acc, 1),
fail
;
nb_accumulator_value(Acc, V)
).

18
packages/CLPBN/pfl.yap
View File

@ -11,6 +11,8 @@
factor/6,
skolem/2,
defined_in_factor/2,
defined_in_factor/3,
evidence/2,
get_pfl_cpt/5, % given id and keys, return new keys and cpt
get_pfl_parameters/3, % given id return par factor parameter
new_pfl_parameters/3, % given id set new parameters
@ -77,6 +79,12 @@ user:term_expansion( Goal, [] ) :-
(ground(Goal) -> true ; throw(error('non ground evidence',Goal))),
% prolog_load_context(module, M),
assert(pfl:evidence(Sk,Var)).
user:term_expansion( Goal, [] ) :-
skolem( Goal, Dom),
( Dom == [f,t] -> true ; throw(error('evidence for what value?',Goal))),
(ground(Goal) -> true ; throw(error('non ground evidence',Goal))),
% prolog_load_context(module, M),
assert(pfl:evidence(Goal,1)).
Id@N :-
generate_entity(0, N, Id, G),
@ -104,6 +112,15 @@ defined_in_factor(Key, Factor) :-
Factor = factor(markov, Id, FList, FV, Phi, Constraints).
defined_in_factor(Key, Id, 0) :-
skolem_in(Key, Id),
factor(bayes, Id, [Key|_FList], _FV, _Phi, _Constraints), !.
defined_in_factor(Key, Id, I) :-
skolem_in(Key, Id),
factor(markov, Id, FList, _FV, _Phi, _Constraints),
nth0(I, FList, Key).
generate_entity(N, N, _, _) :- !.
generate_entity(I0, _N, Id, T) :-
atomic_concat(p, I0, P),
@ -192,7 +209,6 @@ add_evidence(Sk,Var) :-
get_pfl_cpt(Id, Keys, Ev, NewKeys, Out) :-
factor(_Type,Id,[Key|_],_FV,avg,_Constraints), !,
Keys = [Key|Parents],
writeln(Key:Parents),
avg_factors(Key, Parents, 0.0, Ev, NewKeys, Out).
get_pfl_cpt(Id, Keys, _, Keys, Out) :-
factor(_Type,Id,Keys,_FV,Phi,_Constraints),