r + lbfhs
This commit is contained in:
Vitor Santos Costa
parent
134288da68
commit
c04298c1d7
@ -147,6 +147,7 @@ int main(int argc, char **argv)
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YAP_Reset(YAP_FULL_RESET, false);
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/* End preprocessor code */
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mtrace();
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bool rc = exec_top_level(BootMode, &init_args);
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if (!rc)
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return 1;
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@ -20,14 +20,19 @@ class yap4r {
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std::vector<YAPTerm> args;
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bool failed;
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public:
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SEXP qsexp;
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yap4r();
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bool query(std::string p_name,std::string p_module,Rcpp::GenericVector sexps);
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bool query(std::string p_name, GenericVector sexps=R_NilValue, std::string p_module="user");
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bool more();
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bool done();
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SEXP peek(int i);
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bool compile(std::string s);
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bool library(std::string s);
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};
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yap4r::yap4r() {
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YAPEngineArgs *yargs = new YAPEngineArgs();
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yap = new YAPEngine(yargs);
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@ -36,25 +41,29 @@ public:
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bool yap4r::query(std::string p_name,std::string p_module,Rcpp::GenericVector sexps) {
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bool yap4r::query(std::string p_name, GenericVector sexps, std::string p_module) {
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if (q) {
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q->close();
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q = nullptr;
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}
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std::vector<Term> args = std::vector<Term>();
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yhandle_t t;
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arity_t arity;
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if (sexps.isNULL()) {
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YAPTerm qt = YAPAtomTerm(p_name.c_str());
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q = new YAPQuery(qt);
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t =qt.handle();
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} else {
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arity = sexps.length();
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std::vector<YAPTerm> args = std::vector<YAPTerm>();
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yhandle_t sls = Yap_NewHandles(sexps.length());
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for (int i=0; i<sexps.length();i++) {
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if (!sexp_to_pl(sls+i, sexps[i]))
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return false;
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args.push_back( Yap_GetFromSlot(sls+i) );
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args.push_back( YAPTerm(Yap_GetFromSlot(sls+i)) );
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}
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if (i==0) {
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YAPTerm qt = YAPAtomTerm(p_name);
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q = new YAPQuery(qt);
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} else {
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YAPFunctor f= YAPFunctor(p_name, args.length());
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YAPAtomTerm mod = YAPAtomTerm(p_module);
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YAPFunctor f= YAPFunctor(p_name.c_str(), arity);
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YAPAtomTerm mod = YAPAtomTerm(p_module.c_str());
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t = YAPApplTerm(p_name.c_str(),args.data()).handle();
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q = new YAPQuery(f,mod,args.data());
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}
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if (q == nullptr)
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@ -64,10 +73,25 @@ public:
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failed = true;
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q = nullptr;
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}
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return true;
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if(rc)
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qsexp = term_to_sexp(t, false);
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return rc;
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}
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bool yap4r::compile(std::string s) {
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YAPTerm fs[1];
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fs[0] = YAPAtomTerm(s.c_str());
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return yap->mgoal(YAPApplTerm("compile",fs).term(), USER_MODULE);
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}
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bool yap4r::library(std::string s) {
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YAPTerm fs[1], l[1];
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l[0] = YAPAtomTerm(s.c_str());
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fs[0] = YAPApplTerm("library", l);
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return yap->mgoal(YAPApplTerm("compile",fs).term(), USER_MODULE);
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}
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bool yap4r::more() {
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bool rc = true;
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@ -96,6 +120,8 @@ public:
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SEXP yap4r::peek(int i) {
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if (failed || q==nullptr)
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return R_MissingArg;
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if (i==0)
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return qsexp;
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return term_to_sexp(Yap_InitSlot(Yap_XREGS[i]), false);
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}
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@ -106,6 +132,8 @@ public:
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.method( "query", &yap4r::query, "create an active query within the engine")
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.method( "more", &yap4r::more, "ask for an extra solution")
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.method( "done", &yap4r::done, "terminate the query")
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.method( "compile", &yap4r::compile, "compile the file")
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.method( "library", &yap4r::library, "compile the library")
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.method( "peek", &yap4r::peek, "load arg[i] into R")
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;
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}
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@ -26,10 +26,9 @@
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lbfgs_finalize/1,
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lbfgs_set_parameter/3,
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lbfgs_get_parameter/3,
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lbfgs_parameters/0,
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lbfgs_parameters/1]).
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lbfgs_set_parameter/2,
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lbfgs_get_parameter/2,
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lbfgs_parameters/0]).
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% switch on all the checks to reduce bug searching time
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% :- yap_flag(unknown,error).
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@ -187,12 +186,12 @@ lbfgs_finalize(t(_N,X,_U,Params)) :-
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run the algorithm. output the final score of the function being optimised
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*/
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lbfgs_run(t(N,X,U,Params),FX) :-
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lbfgs(N,X, Params, U, FX).
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lbfgs_run(t(N,X,U),FX) :-
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lbfgs(N,X, U, FX).
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/** @pred lbfgs_parameters/1
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/** @pred lbfgs_parameters/0
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Prints a table with the current parameters. See the <a href="http://www.chokkan.org/software/liblbfgs/structlbfgs__parameter__t.html#_details">documentation
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of libLBFGS</a> for the meaning of each parameter.
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@ -220,47 +219,43 @@ int orthantwise_end -1 End index for computing the L1 norm
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~~~~
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*/
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lbfgs_parameters :-
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lbfgs_defaults(Params),
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lbfgs_parameters(t(_X,_,_,Params)).
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lbfgs_parameters(t(_,_,_,Params)) :-
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lbfgs_get_parameter(m,M ,Params),
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lbfgs_get_parameter(epsilon,Epsilon ,Params),
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lbfgs_get_parameter(past,Past ,Params),
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lbfgs_get_parameter(delta,Delta ,Params),
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lbfgs_get_parameter(max_iterations,Max_Iterations ,Params),
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lbfgs_get_parameter(linesearch,Linesearch ,Params),
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lbfgs_get_parameter(max_linesearch,Max_Linesearch ,Params),
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lbfgs_get_parameter(min_step,Min_Step ,Params),
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lbfgs_get_parameter(max_step,Max_Step ,Params),
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lbfgs_get_parameter(ftol,Ftol ,Params),
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lbfgs_get_parameter(gtol,Gtol ,Params),
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lbfgs_get_parameter(xtol,Xtol ,Params),
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lbfgs_get_parameter(orthantwise_c,Orthantwise_C ,Params),
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lbfgs_get_parameter(orthantwise_start,Orthantwise_Start ,Params),
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lbfgs_get_parameter(orthantwise_end,Orthantwise_End ,Params),
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lbfgs_get_parameter(m,M ),
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lbfgs_get_parameter(epsilon,Epsilon ),
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lbfgs_get_parameter(past,Past ),
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lbfgs_get_parameter(delta,Delta ),
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lbfgs_get_parameter(max_iterations,Max_Iterations ),
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lbfgs_get_parameter(linesearch,Linesearch ),
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lbfgs_get_parameter(max_linesearch,Max_Linesearch ),
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lbfgs_get_parameter(min_step,Min_Step ),
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lbfgs_get_parameter(max_step,Max_Step ),
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lbfgs_get_parameter(ftol,Ftol ),
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lbfgs_get_parameter(gtol,Gtol ),
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lbfgs_get_parameter(xtol,Xtol ),
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lbfgs_get_parameter(orthantwise_c,Orthantwise_C ),
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lbfgs_get_parameter(orthantwise_start,Orthantwise_Start ),
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lbfgs_get_parameter(orthantwise_end,Orthantwise_End ),
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format('/******************************************************************************************~n',[] ),
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print_param('Name','Value','Description','Type' ,Params),
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print_param('Name','Value','Description','Type' ),
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format('******************************************************************************************~n',[] ),
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print_param(m,M,'The number of corrections to approximate the inverse hessian matrix.',int ,Params),
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print_param(epsilon,Epsilon,'Epsilon for convergence test.',float ,Params),
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print_param(past,Past,'Distance for delta-based convergence test.',int ,Params),
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print_param(delta,Delta,'Delta for convergence test.',float ,Params),
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print_param(max_iterations,Max_Iterations,'The maximum number of iterations',int ,Params),
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print_param(linesearch,Linesearch,'The line search algorithm.',int ,Params),
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print_param(max_linesearch,Max_Linesearch,'The maximum number of trials for the line search.',int ,Params),
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print_param(min_step,Min_Step,'The minimum step of the line search routine.',float ,Params),
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print_param(max_step,Max_Step,'The maximum step of the line search.',float ,Params),
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print_param(ftol,Ftol,'A parameter to control the accuracy of the line search routine.',float ,Params),
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print_param(gtol,Gtol,'A parameter to control the accuracy of the line search routine.',float ,Params),
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print_param(xtol,Xtol,'The machine precision for floating-point values.',float ,Params),
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print_param(orthantwise_c,Orthantwise_C,'Coefficient for the L1 norm of variables',float ,Params),
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print_param(orthantwise_start,Orthantwise_Start,'Start index for computing the L1 norm of the variables.',int ,Params),
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print_param(orthantwise_end,Orthantwise_End,'End index for computing the L1 norm of the variables.',int ,Params),
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print_param(m,M,'The number of corrections to approximate the inverse hessian matrix.',int ),
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print_param(epsilon,Epsilon,'Epsilon for convergence test.',float ),
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print_param(past,Past,'Distance for delta-based convergence test.',int ),
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print_param(delta,Delta,'Delta for convergence test.',float ),
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print_param(max_iterations,Max_Iterations,'The maximum number of iterations',int ),
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print_param(linesearch,Linesearch,'The line search algorithm.',int ),
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print_param(max_linesearch,Max_Linesearch,'The maximum number of trials for the line search.',int ),
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print_param(min_step,Min_Step,'The minimum step of the line search routine.',float ),
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print_param(max_step,Max_Step,'The maximum step of the line search.',float ),
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print_param(ftol,Ftol,'A parameter to control the accuracy of the line search routine.',float ),
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print_param(gtol,Gtol,'A parameter to control the accuracy of the line search routine.',float ),
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print_param(xtol,Xtol,'The machine precision for floating-point values.',float ),
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print_param(orthantwise_c,Orthantwise_C,'Coefficient for the L1 norm of variables',float ),
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print_param(orthantwise_start,Orthantwise_Start,'Start index for computing the L1 norm of the variables.',int ),
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print_param(orthantwise_end,Orthantwise_End,'End index for computing the L1 norm of the variables.',int ),
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format('******************************************************************************************/~n',[]),
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format(' use lbfgs_set_parameter(Name,Value,Solver) to change parameters~n',[]),
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format(' use lbfgs_get_parameter(Name,Value,Solver) to see current parameters~n',[]),
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format(' use lbfgs_set_parameter(Name,Value) to change parameters~n',[]),
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format(' use lbfgs_get_parameter(Name,Value) to see current parameters~n',[]),
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format(' use lbfgs_parameters to print this overview~2n',[]).
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@ -39,14 +39,14 @@ static lbfgsfloatval_t evaluate(void *instance, const lbfgsfloatval_t *x,
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YAP_Term call;
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YAP_Bool result;
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lbfgsfloatval_t rc;
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YAP_Term v;
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YAP_Term v, t1, t12;
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YAP_Term t[6], t2[2];
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t[0] = v = YAP_MkVarTerm();
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t[1] = YAP_MkIntTerm((YAP_Int)x);
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t[1] = YAP_MkApplTerm(ffloats, 1, t + 1);
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t[2] = YAP_MkIntTerm((YAP_Int)g_tmp);
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t[2] = YAP_MkApplTerm(ffloats, 1, t + 2);
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t1 = YAP_MkIntTerm((YAP_Int)x);
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t[1] = YAP_MkApplTerm(ffloats, 1, &t1);
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t12 = YAP_MkIntTerm((YAP_Int)g_tmp);
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t[2] = YAP_MkApplTerm(ffloats, 1, &t12);
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t[3] = YAP_MkIntTerm(n);
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t[4] = YAP_MkFloatTerm(step);
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t[5] = YAP_MkIntTerm((YAP_Int)instance);
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@ -310,8 +310,10 @@ static YAP_Bool p_lbfgs(void) {
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s = "A logic error (negative line-search step) occurred.";
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break;
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}
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fprintf(stderr, "optimization terminated with code %d: %s\n", ret, s);
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char ss[1024];
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snprintf(ss, 1023, "optimization terminated with code %d: %s\n", ret, s);
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fputs(ss, stderr);
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return true;
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}
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@ -326,16 +328,8 @@ static YAP_Bool lbfgs_grab(void) {
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return YAP_Unify(YAP_ARG2, YAP_MkApplTerm(ffloats, 1, &t));
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}
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static YAP_Bool lbfgs_parameters(void) {
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lbfgs_parameter_t *x = malloc(sizeof(lbfgs_parameter_t));
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lbfgs_parameter_init(x);
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return YAP_Unify(YAP_ARG1, YAP_MkIntTerm((YAP_Int)x));
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}
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static lbfgs_parameter_t parms;
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static YAP_Bool lbfgs_release_parameters(void) {
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free((void *)YAP_IntOfTerm(YAP_ARG1));
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return true;
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}
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static YAP_Bool lbfgs_release(void) {
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/* if (lbfgs_status == LBFGS_STATUS_NONE) { */
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@ -349,11 +343,11 @@ static YAP_Bool lbfgs_release(void) {
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return TRUE;
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/* return FALSE; */
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}
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static YAP_Bool lbfgs_defaults(void) {
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static lbfgs_parameter_t *get_params(YAP_Term t) {
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YAP_Int ar = YAP_ArityOfFunctor(YAP_FunctorOfTerm(t));
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YAP_Term arg = YAP_ArgOfTerm(ar, t);
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return (lbfgs_parameter_t *)YAP_IntOfTerm(arg);
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lbfgs_parameter_init(&parms);
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return TRUE;
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/* return FALSE; */
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}
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/** @pred lbfgs_set_parameter(+Name,+Value,+Parameters)
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@ -363,7 +357,7 @@ is not running.
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static YAP_Bool lbfgs_set_parameter(void) {
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YAP_Term t1 = YAP_ARG1;
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YAP_Term t2 = YAP_ARG2;
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lbfgs_parameter_t *param = get_params(YAP_ARG3);
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lbfgs_parameter_t *param = &parms;
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/* if (lbfgs_status != LBFGS_STATUS_NONE && lbfgs_status !=
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* LBFGS_STATUS_INITIALIZED){ */
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/* printf("ERROR: Lbfgs is running right now. Please wait till it is
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@ -523,9 +517,9 @@ Get the current Value for Name
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static YAP_Bool lbfgs_get_parameter(void) {
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YAP_Term t1 = YAP_ARG1;
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YAP_Term t2 = YAP_ARG2;
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lbfgs_parameter_t *param = get_params(YAP_ARG3);
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lbfgs_parameter_t *param = &parms;
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if (!YAP_IsAtomTerm(t1)) {
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if (!YAP_IsAtomTerm(t1)) {
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return FALSE;
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}
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@ -575,14 +569,14 @@ X_API void init_lbfgs_predicates(void) {
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tuser = YAP_MkAtomTerm(YAP_LookupAtom("user"));
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// Initialize the parameters for the L-BFGS optimization.
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// lbfgs_parameter_init(¶m);
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lbfgs_parameter_init(&parms);
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YAP_UserCPredicate("lbfgs_grab", lbfgs_grab, 2);
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YAP_UserCPredicate("lbfgs", p_lbfgs, 5);
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YAP_UserCPredicate("lbfgs_release", lbfgs_release, 1);
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YAP_UserCPredicate("lbfgs_defaults", lbfgs_parameters, 1);
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YAP_UserCPredicate("lbfgs_release_parameters", lbfgs_release_parameters, 1);
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YAP_UserCPredicate("lbfgs_set_parameter", lbfgs_set_parameter, 3);
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YAP_UserCPredicate("lbfgs_get_parameter", lbfgs_get_parameter, 3);
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YAP_UserCPredicate("lbfgs_defaults", lbfgs_defaults, 0);
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YAP_UserCPredicate("lbfgs_set_parameter", lbfgs_set_parameter, 2);
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YAP_UserCPredicate("lbfgs_get_parameter", lbfgs_get_parameter, 2);
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}
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