speedup.
This commit is contained in:
Vitor Santos Costa
parent
7458d8ee74
commit
15bcaf97fc
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@ -620,6 +620,7 @@ init_one_query(QueryID,Query,Type) :-
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rb_new(H0),
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maplist_to_hash(MapList, H0, Hash),
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tree_to_grad(Tree, Hash, [], Grad),
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%% %writeln(Call:Tree),
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recordz(QueryID,bdd(Grad,MapList),_)
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)
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),
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@ -712,15 +713,10 @@ gradient(QueryID, l, Slope) :-
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fail.
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gradient(_QueryID, l, _).
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gradient(QueryID, g, Slope) :-
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/*
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query_gradient(17,x2,p,6.736196e-02).
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query_probability(17,1.173512e-01).
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*/
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recorded(QueryID, bdd(Tree, MapList), _),
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bind_maplist(MapList),
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member(I-_, MapList),
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run_grad(Tree, I, Slope, 0.0, Grad),
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% writeln(query_gradient_intern(QueryID,I,p,Grad)),
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assert(query_gradient_intern(QueryID,I,p,Grad)),
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fail.
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gradient(QueryID, g, Slope) :-
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@ -827,6 +823,8 @@ query_probability(QueryID,Prob) :-
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query_probability_intern(OtherQueryID,Prob)
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)
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).
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query_gradient(QueryID,Fact,p,Value) :- !,
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query_gradient_intern(QueryID,Fact,p,Value).
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query_gradient(QueryID,Fact,Type,Value) :-
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(
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query_gradient_intern(QueryID,Fact,Type,Value)
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@ -1079,7 +1077,9 @@ add_gradient(Learning_Rate) :-
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retractall(values_correct).
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% vsc: avoid silly search
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gradient_descent :-
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continuous_fact(_), !,
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current_iteration(Iteration),
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create_training_predictions_file_name(Iteration,File_Name),
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open(File_Name,'write',Handle),
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@ -1288,6 +1288,173 @@ gradient_descent :-
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!,
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forget_old_probabilities.
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% VSC: no continuous facts
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% simplify code
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gradient_descent :-
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current_iteration(Iteration),
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create_training_predictions_file_name(Iteration,File_Name),
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open(File_Name,'write',Handle),
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format(Handle,"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%~n",[]),
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format(Handle,"% Iteration, train/test, QueryID, Query, GroundTruth, Prediction %~n",[]),
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format(Handle,"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%~n",[]),
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format_learning(2,'Gradient ',[]),
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save_old_probabilities,
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update_values,
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% start set gradient to zero
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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forall(tunable_fact(FactID,_),
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(
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(
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atomic_concat(['grad_',FactID],Key),
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bb_put(Key,0.0)
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)
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)
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),
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% stop gradient to zero
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% start calculate gradient
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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bb_put(mse_train_sum, 0.0),
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bb_put(mse_train_min, 0.0),
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bb_put(mse_train_max, 0.0),
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bb_put(llh_training_queries, 0.0),
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problog_flag(alpha,Alpha),
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logger_set_variable(alpha,Alpha),
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example_count(Example_Count),
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forall(user:example(QueryID,Query,QueryProb,Type),
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(
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once(update_query(QueryID,'.',all)),
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query_probability(QueryID,BDDProb),
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format(Handle,'ex(~q,train,~q,~q,~10f,~10f).~n',[Iteration,QueryID,Query,QueryProb,BDDProb]),
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(
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QueryProb=:=0.0
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->
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Y2=Alpha;
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Y2=1.0
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),
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(
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(Type == '='; (Type == '<', BDDProb>QueryProb); (Type=='>',BDDProb<QueryProb))
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->
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Y is Y2*2/Example_Count * (BDDProb-QueryProb);
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Y=0.0
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),
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% first do the calculations for the MSE on training set
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(
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(Type == '='; (Type == '<', BDDProb>QueryProb); (Type=='>',BDDProb<QueryProb))
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->
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Squared_Error is (BDDProb-QueryProb)**2;
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Squared_Error=0.0
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),
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bb_get(mse_train_sum,Old_MSE_Train_Sum),
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bb_get(mse_train_min,Old_MSE_Train_Min),
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bb_get(mse_train_max,Old_MSE_Train_Max),
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bb_get(llh_training_queries,Old_LLH_Training_Queries),
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New_MSE_Train_Sum is Old_MSE_Train_Sum+Squared_Error,
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New_MSE_Train_Min is min(Old_MSE_Train_Min,Squared_Error),
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New_MSE_Train_Max is max(Old_MSE_Train_Max,Squared_Error),
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New_LLH_Training_Queries is Old_LLH_Training_Queries+log(BDDProb),
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bb_put(mse_train_sum,New_MSE_Train_Sum),
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bb_put(mse_train_min,New_MSE_Train_Min),
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bb_put(mse_train_max,New_MSE_Train_Max),
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bb_put(llh_training_queries,New_LLH_Training_Queries),
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( % go over all tunable facts
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query_gradient(QueryID,FactID,p,GradValue),
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atomic_concat(['grad_',FactID],Key),
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bb_get(Key,OldValue),
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NewValue is OldValue + Y*GradValue,
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bb_put(Key,NewValue),
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fail; % go to next fact
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true
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),
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once(update_query_cleanup(QueryID))
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)),
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% stop calculate gradient
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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!,
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close(Handle),
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% start statistics on gradient
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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findall(V, (
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tunable_fact(FactID,_),
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atomic_concat(['grad_',FactID],Key),
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bb_get(Key,V)
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),Gradient_Values),
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(
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Gradient_Values==[]
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->
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(
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logger_set_variable(gradient_mean,0.0),
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logger_set_variable(gradient_min,0.0),
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logger_set_variable(gradient_max,0.0)
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);
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(
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sum_list(Gradient_Values,GradSum),
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max_list(Gradient_Values,GradMax),
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min_list(Gradient_Values,GradMin),
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length(Gradient_Values,GradLength),
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GradMean is GradSum/GradLength,
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logger_set_variable(gradient_mean,GradMean),
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logger_set_variable(gradient_min,GradMin),
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logger_set_variable(gradient_max,GradMax)
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)
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),
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% stop statistics on gradient
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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bb_delete(mse_train_sum,MSE_Train_Sum),
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bb_delete(mse_train_min,MSE_Train_Min),
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bb_delete(mse_train_max,MSE_Train_Max),
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bb_delete(llh_training_queries,LLH_Training_Queries),
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MSE is MSE_Train_Sum/Example_Count,
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logger_set_variable(mse_trainingset,MSE),
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logger_set_variable(mse_min_trainingset,MSE_Train_Min),
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logger_set_variable(mse_max_trainingset,MSE_Train_Max),
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logger_set_variable(llh_training_queries,LLH_Training_Queries),
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format_learning(2,'~n',[]),
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% start add gradient to current probabilities
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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(
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problog_flag(line_search,false)
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->
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problog_flag(learning_rate,LearningRate);
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lineSearch(LearningRate,_)
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),
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format_learning(3,'learning rate:~8f~n',[LearningRate]),
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add_gradient(LearningRate),
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logger_set_variable(learning_rate,LearningRate),
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% stop add gradient to current probabilities
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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!,
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forget_old_probabilities.
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%========================================================================
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%=
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%=
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