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Merge branch 'master' of ssh://yap.git.sourceforge.net/gitroot/yap/yap-6.3

Browse Source 
Conflicts:
	packages/jpl
This commit is contained in:
Vítor Santos Costa 2012-07-07 09:54:27 -05:00
commit bc8c9a423a
15 changed files with 207 additions and 85 deletions
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7
C/stdpreds.c
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@ -3256,21 +3256,20 @@ cont_current_predicate_for_atom( USES_REGS1 )
}
p = RepPredProp(p->NextOfPE);
}
READ_UNLOCK(PredHashRWLock);
}
}
READ_UNLOCK(pp->FRWLock);
} else if (pp->KindOfPE == PEProp) {
PredEntry *pe = RepPredProp(pf);
READ_LOCK(pp->FRWLock);
PELOCK(31,pe);
if (pe->ModuleOfPred == mod ||
pe->ModuleOfPred == 0) {
/* we found the predicate */
EXTRA_CBACK_ARG(3,1) = MkIntegerTerm((Int)(pp->NextOfPE));
READ_UNLOCK(pp->FRWLock);
UNLOCKPE(31,pe);
return Yap_unify(ARG3,MkIntTerm(0));
}
READ_UNLOCK(pp->FRWLock);
UNLOCKPE(31,pe);
}
pf = pp->NextOfPE;
}

1
H/inline-only.h
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@ -3,6 +3,7 @@
#ifdef __GNUC__
#define INLINE_ONLY __attribute__((gnu_inline,always_inline))
//#define INLINE_ONLY
#else
#define INLINE_ONLY
#endif

2
packages/CLPBN/clpbn.yap
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@ -122,7 +122,7 @@
:- dynamic solver/1,output/1,use/1,suppress_attribute_display/1, parameter_softening/1, em_solver/1, use_parfactors/1.
solver(ve).
em_solver(ve).
em_solver(bp).
:- meta_predicate probability(:,-), conditional_probability(:,:,-).

2
packages/CLPBN/clpbn/ground_factors.yap
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@ -61,7 +61,7 @@ ground_all_keys([], _).
ground_all_keys([V|GVars], AllKeys) :-
clpbn:get_atts(V,[key(Key)]),
\+ ground(Key), !,
wroteln(g:Key),
writeln(g:Key),
member(Key, AllKeys),
ground_all_keys(GVars, AllKeys).
ground_all_keys([_V|GVars], AllKeys) :-

88
packages/CLPBN/clpbn/horus_ground.yap
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@ -52,25 +52,40 @@
call_horus_ground_solver(QueryVars, QueryKeys, AllKeys, Factors, Evidence, Output) :-
b_hash_new(Hash0),
keys_to_ids(AllKeys, 0, Hash0, Hash),
get_factors_type(Factors, Type),
evidence_to_ids(Evidence, Hash, EvidenceIds),
factors_to_ids(Factors, Hash, FactorIds),
%writeln(type:Type), writeln(''),
%writeln(allKeys:AllKeys), writeln(''),
%sort(AllKeys,SKeys),writeln(allKeys:SKeys), writeln(''),
%writeln(factors:Factors), writeln(''),
%writeln(factorIds:FactorIds), writeln(''),
%writeln(evidence:Evidence), writeln(''),
%writeln(evidenceIds:EvidenceIds), writeln(''),
cpp_create_ground_network(Type, FactorIds, EvidenceIds, Network),
%get_vars_information(AllKeys, StatesNames),
%terms_to_atoms(AllKeys, KeysAtoms),
%cpp_set_vars_information(KeysAtoms, StatesNames),
run_solver(ground(Network,Hash), QueryKeys, Solutions),
clpbn_bind_vals([QueryVars], Solutions, Output),
cpp_free_ground_network(Network).
call_horus_ground_solver_for_probabilities(QueryKeys, AllKeys, Factors, Evidence, Solutions),
clpbn_bind_vals([QueryVars], Solutions, Output).
call_horus_ground_solver_for_probabilities(QueryKeys, _AllKeys, Factors, Evidence, Solutions) :-
attributes:all_attvars(AVars),
keys(AVars, AllKeys),
b_hash_new(Hash0),
keys_to_ids(AllKeys, 0, Hash0, Hash),
get_factors_type(Factors, Type),
evidence_to_ids(Evidence, Hash, EvidenceIds),
factors_to_ids(Factors, Hash, FactorIds),
writeln(queryKeys:QueryKeys), writeln(''),
writeln(type:Type), writeln(''),
writeln(allKeys:AllKeys), writeln(''),
sort(AllKeys,SKeys),writeln(allSortedKeys:SKeys), writeln(''),
keys_to_ids(SKeys, 0, Hash0, Hash),
writeln(factors:Factors), writeln(''),
writeln(factorIds:FactorIds), writeln(''),
writeln(evidence:Evidence), writeln(''),
writeln(evidenceIds:EvidenceIds), writeln(''),
cpp_create_ground_network(Type, FactorIds, EvidenceIds, Network),
get_vars_information(AllKeys, StatesNames),
terms_to_atoms(AllKeys, KeysAtoms),
cpp_set_vars_information(KeysAtoms, StatesNames),
run_solver(ground(Network,Hash), QueryKeys, Solutions),
cpp_free_ground_network(Network).
keys([], []).
keys([V|AVars], [K|AllKeys]) :-
clpbn:get_atts(V,[key(K)]), !,
keys(AVars, AllKeys).
keys([_V|AVars], AllKeys) :-
keys(AVars, AllKeys).
run_solver(ground(Network,Hash), QueryKeys, Solutions) :-
@ -94,9 +109,13 @@ get_factors_type([f(markov, _, _, _)|_], markov) :- ! .
list_of_keys_to_ids([], _, []).
list_of_keys_to_ids([List|Extra], Hash, [IdList|More]) :-
List = [_|_], !,
list_of_keys_to_ids(List, Hash, IdList),
list_of_keys_to_ids(Extra, Hash, More).
list_of_keys_to_ids([Key|QueryKeys], Hash, [Id|QueryIds]) :-
b_hash_lookup(Key, Id, Hash),
list_of_keys_to_ids(QueryKeys, Hash, QueryIds).
b_hash_lookup(Key, Id, Hash),
list_of_keys_to_ids(QueryKeys, Hash, QueryIds).
factors_to_ids([], _, []).
@ -134,10 +153,33 @@ terms_to_atoms(K.Ks, Atom.As) :-
finalize_horus_ground_solver(bp(Network, _)) :-
cpp_free_ground_network(Network).
%
% QVars: all query variables?
%
%
init_horus_ground_solver(QueryVars, _AllVars, _, horus(GKeys, Keys, Factors, Evidence)) :-
trace,
generate_networks(QueryVars, GKeys, [], Keys, [], Factors, [], Evidence),
writeln(qvs:QueryVars),
writeln(Keys), !.
init_horus_ground_solver(_, _AllVars0, _, bp(_BayesNet, _DistIds)) :- !.
%
% as you add query vars the network grows
% until you reach the last variable.
%
generate_networks([QVars|QueryVars], [GK|GKeys], _K0, K, _F0, F, _E0, E) :-
clpbn:generate_network(QVars, GK, KI, FI, EI),
generate_networks(QueryVars, GKeys, KI, K, FI, F, EI, E).
generate_networks([], [], K, K, F, F, E, E).
run_horus_ground_solver(_QueryVars, _Solutions, bp(_Network, _DistIds)) :- !.
%
% just call horus solver.
%
run_horus_ground_solver(_QueryVars, Solutions, horus(GKeys, Keys, Factors, Evidence) ) :- !,
writeln(sols:Solutions),
writeln(state:_State),
trace,
call_horus_ground_solver_for_probabilities(GKeys, Keys, Factors, Evidence, Solutions).
%bp([[]],_,_) :- !.
%bp([QueryVars], AllVars, Output) :-

2
packages/CLPBN/clpbn/horus_lifted.yap
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@ -2,7 +2,7 @@
Interface to Horus Lifted Solvers. Used by:
- Lifted Variable Elimination
- Lifted First-Order Belief Propagation
********************************************************/
:- module(clpbn_horus_lifted,

1
packages/CLPBN/clpbn/ve.yap
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@ -81,7 +81,6 @@ ve([LVs],Vs0,AllDiffs) :-
init_ve_solver(Qs, Vs0, _, LVis) :-
check_for_agg_vars(Vs0, Vs1),
% LVi will have a list of CLPBN variables
% Tables0 will have the full data on each variable
init_influences(Vs1, G, RG),
init_ve_solver_for_questions(Qs, G, RG, _, LVis).

56
packages/CLPBN/examples/learning/prof_params.pfl Normal file
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@ -0,0 +1,56 @@
% learn distribution for school database.
:- use_module(library(pfl)).
:- use_module(library(clpbn/learning/em)).
bayes abi(K)::[h,m,l] ; abi_table ; [professor(K)].
bayes pop(K)::[h,m,l], abi(K) ; pop_table ; [professor(K)].
abi_table([0.3,0.3,0.4]).
pop_table([0.3,0.3,0.4,0.3,0.3,0.4,0.3,0.3,0.4]).
goal_list([/*abi(p0,h),
abi(p1,m),
abi(p2,m),
abi(p3,m),
abi(p4,l),*/
pop(p5,h),
abi(p5,_),
abi(p6,_),
pop(p7,_)]).
professor(p1).
professor(p2).
professor(p3).
professor(p4).
professor(p5).
professor(p6).
professor(p7).
professor(p8).
%:- clpbn:set_clpbn_flag(em_solver,gibbs).
%:- clpbn:set_clpbn_flag(em_solver,jt).
:- clpbn:set_clpbn_flag(em_solver,ve).
%:- clpbn:set_clpbn_flag(em_solver,bp).
timed_main :-
statistics(runtime, _),
main(Lik),
statistics(runtime, [T,_]),
format('Took ~d msec and Lik ~3f~n',[T,Lik]).
main(Lik) :-
goal_list(L),
% run_queries(L),
em(L,0.01,10,_,Lik).
run_queries([]).
run_queries(Q.L) :-
call(Q),
run_queries(L).

2
packages/CLPBN/examples/learning/school_params.yap
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File diff suppressed because one or more lines are too long

8
packages/CLPBN/horus/CountingBp.cpp
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@ -236,7 +236,7 @@ CountingBp::createClusters (
const VarNodes& groupVars = it->second;
VarCluster* vc = new VarCluster (groupVars);
for (size_t i = 0; i < groupVars.size(); i++) {
vid2VarCluster_.insert (make_pair (groupVars[i]->varId(), vc));
varClusterMap_.insert (make_pair (groupVars[i]->varId(), vc));
}
varClusters_.push_back (vc);
}
@ -250,7 +250,7 @@ CountingBp::createClusters (
varClusters.reserve (neighs.size());
for (size_t i = 0; i < neighs.size(); i++) {
VarId vid = neighs[i]->varId();
varClusters.push_back (vid2VarCluster_.find (vid)->second);
varClusters.push_back (varClusterMap_.find (vid)->second);
}
facClusters_.push_back (new FacCluster (it->second, varClusters));
}
@ -294,8 +294,8 @@ CountingBp::getSignature (const FacNode* facNode)
VarId
CountingBp::getRepresentative (VarId vid)
{
assert (Util::contains (vid2VarCluster_, vid));
VarCluster* vc = vid2VarCluster_.find (vid)->second;
assert (Util::contains (varClusterMap_, vid));
VarCluster* vc = varClusterMap_.find (vid)->second;
return vc->representative()->varId();
}

72
packages/CLPBN/horus/CountingBp.h
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@ -10,8 +10,6 @@
class VarCluster;
class FacCluster;
class VarSignHash;
class FacSignHash;
class WeightedBp;
typedef long Color;
@ -22,40 +20,44 @@ typedef vector<Color> FacSignature;
typedef unordered_map<unsigned, Color> DistColorMap;
typedef unordered_map<unsigned, Colors> VarColorMap;
typedef unordered_map<VarSignature, VarNodes, VarSignHash> VarSignMap;
typedef unordered_map<FacSignature, FacNodes, FacSignHash> FacSignMap;
typedef unordered_map<VarSignature, VarNodes> VarSignMap;
typedef unordered_map<FacSignature, FacNodes> FacSignMap;
typedef unordered_map<VarId, VarCluster*> VarClusterMap;
typedef vector<VarCluster*> VarClusters;
typedef vector<FacCluster*> FacClusters;
typedef unordered_map<VarId, VarCluster*> VarId2VarCluster;
struct VarSignHash
template <class T>
inline size_t hash_combine (size_t seed, const T& v)
{
size_t operator() (const VarSignature &sig) const
{
size_t val = hash<size_t>()(sig.size());
for (size_t i = 0; i < sig.size(); i++) {
val ^= hash<size_t>()(sig[i].first);
val ^= hash<size_t>()(sig[i].second);
}
return val;
}
};
return seed ^ (hash<T>()(v) + 0x9e3779b9 + (seed << 6) + (seed >> 2));
}
struct FacSignHash
{
size_t operator() (const FacSignature &sig) const
namespace std {
template <typename T1, typename T2> struct hash<std::pair<T1,T2>>
{
size_t val = hash<size_t>()(sig.size());
for (size_t i = 0; i < sig.size(); i++) {
val ^= hash<size_t>()(sig[i]);
size_t operator() (const std::pair<T1,T2>& p) const
{
return hash_combine (std::hash<T1>()(p.first), p.second);
}
return val;
}
};
};
template <typename T> struct hash<std::vector<T>>
{
size_t operator() (const std::vector<T>& vec) const
{
size_t h = 0;
typename vector<T>::const_iterator first = vec.begin();
typename vector<T>::const_iterator last = vec.end();
for (; first != last; ++first) {
h = hash_combine (h, *first);
}
return h;
}
};
}
class VarCluster
@ -72,8 +74,8 @@ class VarCluster
void setRepresentative (VarNode* vn) { repr_ = vn; }
private:
VarNodes members_;
VarNode* repr_;
VarNodes members_;
VarNode* repr_;
};
@ -86,17 +88,17 @@ class FacCluster
const FacNode* first (void) const { return members_.front(); }
const FacNodes& members (void) const { return members_; }
VarClusters& varClusters (void) { return varClusters_; }
FacNode* representative (void) const { return repr_; }
void setRepresentative (FacNode* fn) { repr_ = fn; }
VarClusters& varClusters (void) { return varClusters_; }
private:
FacNodes members_;
VarClusters varClusters_;
FacNode* repr_;
VarClusters varClusters_;
};
@ -171,9 +173,9 @@ class CountingBp : public Solver
Colors facColors_;
VarClusters varClusters_;
FacClusters facClusters_;
VarId2VarCluster vid2VarCluster_;
VarClusterMap varClusterMap_;
const FactorGraph* compressedFg_;
WeightedBp* solver_;
WeightedBp* solver_;
};
#endif // HORUS_COUNTINGBP_H

33
packages/CLPBN/horus/ElimGraph.cpp
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@ -184,26 +184,43 @@ ElimGraph::getLowestCostNode (void) const
{
EgNode* bestNode = 0;
unsigned minCost = std::numeric_limits<unsigned>::max();
unsigned cost = 0;
EGNeighs::const_iterator it;
switch (elimHeuristic) {
case MIN_NEIGHBORS: {
for (it = unmarked_.begin(); it != unmarked_.end(); ++ it) {
cost = getNeighborsCost (*it);
unsigned cost = getNeighborsCost (*it);
if (cost < minCost) {
bestNode = *it;
minCost = cost;
}
}}
break;
case MIN_WEIGHT:
//cost = getWeightCost (unmarked_[i]);
case MIN_WEIGHT: {
for (it = unmarked_.begin(); it != unmarked_.end(); ++ it) {
unsigned cost = getWeightCost (*it);
if (cost < minCost) {
bestNode = *it;
minCost = cost;
}
}}
break;
case MIN_FILL:
//cost = getFillCost (unmarked_[i]);
case MIN_FILL: {
for (it = unmarked_.begin(); it != unmarked_.end(); ++ it) {
unsigned cost = getFillCost (*it);
if (cost < minCost) {
bestNode = *it;
minCost = cost;
}
}}
break;
case WEIGHTED_MIN_FILL:
//cost = getWeightedFillCost (unmarked_[i]);
case WEIGHTED_MIN_FILL: {
for (it = unmarked_.begin(); it != unmarked_.end(); ++ it) {
unsigned cost = getWeightedFillCost (*it);
if (cost < minCost) {
bestNode = *it;
minCost = cost;
}
}}
break;
default:
assert (false);

6
packages/CLPBN/horus/ElimGraph.h
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@ -130,9 +130,9 @@ class ElimGraph
void connectAllNeighbors (const EgNode*);
vector<EgNode*> nodes_;
TinySet<EgNode*> unmarked_;
unordered_map<VarId, EgNode*> varMap_;
vector<EgNode*> nodes_;
TinySet<EgNode*> unmarked_;
unordered_map<VarId, EgNode*> varMap_;
};
#endif // HORUS_ELIMGRAPH_H

2
packages/CLPBN/horus/TODO
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@ -1,5 +1,3 @@
- Find a way to decrease the time required to find an
elimination order for variable elimination
- Consider using hashs instead of vectors of colors to calculate the groups in
counting bp

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

@ -97,7 +97,7 @@ init_em(Items, state( AllDists, AllDistInstances, MargVars, SolverVars)) :-
em_loop(Its, Likelihood0, State, MaxError, MaxIts, LikelihoodF, FTables) :-
estimate(State, LPs),
maximise(State, Tables, LPs, Likelihood),
% writeln(Likelihood:Its:Likelihood0:Tables),
writeln(iteration:Its:Likelihood:Its:Likelihood0:Tables),
(
(
abs((Likelihood - Likelihood0)/Likelihood) < MaxError
@ -166,6 +166,14 @@ find_variables([K|PKeys], AllVars0, [Parent|Parents]) :-
find_variable(K, AllVars0, Parent),
find_variables(PKeys, AllVars0, Parents).
%
% in clp(bn) the whole network is constructed when you evaluate EM. In
% pfl, we want to delay execution until as late as possible.
% we just create a new variable and hope for the best.
%
%
find_variable(K, [], Parent) :-
clpbn:put_atts(Parent, [key(K)]).
find_variable(K, [Parent|_AllVars0], Parent) :-
clpbn:get_atts(Parent, [key(K0)]), K0 =@= K, !.
find_variable(K, [_|AllVars0], Parent) :-