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Fix finalizing horus ground solvers on EM

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This commit is contained in:
Tiago Gomes 2012-12-17 23:59:52 +00:00
parent 5fa5dda579
commit c7a4adcefb
2 changed files with 14 additions and 11 deletions
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15
packages/CLPBN/clpbn.yap
View File

@ -10,9 +10,9 @@
clpbn_init_graph/1,
clpbn_init_solver/4,
clpbn_run_solver/3,
clpbn_finalize_solver/1,
pfl_init_solver/5,
pfl_run_solver/3,
pfl_end_solver/1,
probability/2,
conditional_probability/3,
use_parfactors/1,
@ -662,17 +662,9 @@ clpbn_run_solver(gibbs, LVs, LPs, State) :-
clpbn_run_solver(pcg, LVs, LPs, State) :-
run_pcg_solver(LVs, LPs, State).
%clpbn_finalize_solver(State) :-
% solver(bp), !,
% functor(State, _, Last),
% arg(Last, State, Info),
% finalize_horus_ground_solver(Info).
clpbn_finalize_solver(_State).
%
% This is a routine to start a solver, called by the learning procedures (ie, em).
%
pfl_init_solver(QueryKeys, AllKeys, Factors, Evidence, State) :-
em_solver(Solver),
(lifted_solver(Solver) ->
@ -729,6 +721,11 @@ pfl_run_solver(LVs, LPs, State, bp) :- !,
pfl_run_solver(LVs, LPs, State, cbp) :- !,
run_horus_ground_solver(LVs, LPs, State).
pfl_end_solver(State) :-
(em_solver(hve) ; em_solver(bp) ; em_solver(cbp)),
finalize_horus_ground_solver(State).
pfl_end_solver(_State).
add_keys(Key1+V1,_Key2,Key1+V1).

10
packages/CLPBN/learning/em.yap
View File

@ -13,9 +13,9 @@
[clpbn_init_graph/1,
clpbn_init_solver/4,
clpbn_run_solver/3,
clpbn_finalize_solver/1,
pfl_init_solver/5,
pfl_run_solver/3,
pfl_end_solver/1,
conditional_probability/3,
clpbn_flag/2
]).
@ -75,7 +75,7 @@
em(Items, MaxError, MaxIts, Tables, Likelihood) :-
catch(init_em(Items, State),Error,handle_em(Error)),
em_loop(0, 0.0, State, MaxError, MaxIts, Likelihood, Tables),
clpbn_finalize_solver(State),
end_em(State),
assert(em_found(Tables, Likelihood)),
fail.
% get rid of new random variables the easy way :)
@ -89,6 +89,12 @@ handle_em(error(repeated_parents)) :- !,
handle_em(Error) :-
throw(Error).
end_em(state(_AllDists, _AllDistInstances, _MargKeys, SolverState)) :-
clpbn:use_parfactors(on), !,
pfl_end_solver(SolverState).
end_em(_).
% This gets you an initial configuration. If there is a lot of evidence
% tables may be filled in close to optimal, otherwise they may be
% close to uniform.