prepare merge

packages/ProbLog/problog_lbfgs.yap

@@ -848,38 +848,42 @@ set_tunable(I,Slope,P) :-
 	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 user:evaluate(LLH_Training_Queries, X,Grad,N,_,_) :-
     %Handle = user_error,
-    GradCount <== array[N] of ints,
+    example_count(TrainingExampleCount),
+    LLs <== array[TrainingExampleCount ] of floats,
     Probs  <== array[N] of floats,
     problog_flag(sigmoid_slope,Slope),
-    N1 is N-1,
-    
+    N1 is N-1,    
     forall(between(0,N1,I),
-	   (Grad[I] <== 0.0, S <== X[I], sigmoid(S,Slope, P), Probs[I] <== P) 
-	  ),
-    findall(LL,
-	    compute_grad(Grad, GradCount, Probs, Slope, LL),
-	    LLs
-	   ),
-    sum_list(LLs,LLH_Training_Queries).
+	   (Grad[I] <== 0.0, S <== X[I], sigmoid(S,Slope, P), Probs[I] <== P)
+	  ), nl,
+    forall( 
+	full_example(QueryID,QueryProb,BDD),	   
+	   compute_grad(QueryID, BDD, QueryProb,Grad, Probs, Slope,LLs)
+    ),
+    LLH_Training_Queries <== sum(LLs),
+    writeln(LLH_Training_Queries).
 %wrap(X, Grad, GradCount).
 
+full_example(QueryID,QueryProb,BDD) :-
+    user:example(QueryID,_Query,QueryProb,_),
+     recorded(QueryID,BDD,_),
+         BDD = bdd(_Dir, _GradTree, MapList),
+         MapList = [_|_].
 
-compute_grad(Grad, GradCount, Probs, Slope, LL) :-
-	user:example(QueryID,_Query,QueryProb,_),
-	recorded(QueryID,BDD,_),
-	BDD = bdd(_Dir, _GradTree, MapList),
-	MapList = [_|_],
-	bind_maplist(MapList, Slope, Probs),
-%writeln( MapList ),
+compute_grad(QueryID,BDD,QueryProb, Grad, Probs, Slope, LLs) :-
+    BDD = bdd(_Dir, _GradTree, MapList),
+    bind_maplist(MapList, Slope, Probs),
+    recorded(QueryID,BDD,_),
     qprobability(BDD,Slope,BDDProb),
-    LL is (((BDDProb)-(QueryProb))**2),
+    LL is (BDDProb-QueryProb)*(BDDProb-QueryProb),
+    LLs[QueryID] <== LL,    
 %writeln( qprobability(BDD,Slope,BDDProb) ),
     forall(
 	    member(I-_, MapList),
-	gradientpair(I, BDD,Slope,BDDProb, QueryProb, Grad, Probs, GradCount)
+	gradientpair(I, BDD,Slope,BDDProb, QueryProb, Grad, Probs)
     ).
 
-gradientpair(I, BDD,Slope,BDDProb, QueryProb, Grad, Probs, 	GradCount) :-
+gradientpair(I, BDD,Slope,BDDProb, QueryProb, Grad, Probs) :-
     qgradient(I, BDD, Slope, FactID, GradValue),
     % writeln(FactID),
     G0 <== Grad[FactID],
@@ -887,10 +891,7 @@ gradientpair(I, BDD,Slope,BDDProb, QueryProb, Grad, Probs, 	GradCount) :-
 %writeln(    GN is G0-GradValue*(QueryProb-BDDProb)),
    GN is G0-GradValue*2*Prob*(1-Prob)*(QueryProb-BDDProb),
    %writeln(FactID:(G0->GN)),
-   GC <== GradCount[FactID],
-   GC1 is GC+1,
-   GradCount[FactID] <== GC1,
-    Grad[FactID] <== GN.
+Grad[FactID] <== GN.
 
 qprobability(bdd(Dir, Tree, _MapList), Slope, Prob) :-
 /*	query_probability(21,6.775948e-01). */

packages/python/yap_kernel/yap_ipython/yapi.py

@@ -835,5 +835,5 @@ class YAPRun:
         (query, _,loop, sols) = self.clean_end(query)
         return (program, query, loop, sols)
 
-global
-globals = {}
+# global
+#globals = {}