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#include "global_data.h"
#include "parser.h"
#include "learner.h"
void save_predictor(vw& all, string reg_name, size_t current_pass);
namespace LEARNER
{
void generic_driver(vw* all)
{
example* ec = NULL;
all->l->init_driver();
while ( true )
{
if ((ec = VW::get_example(all->p)) != NULL)//semiblocking operation.
{
if (ec->indices.size() > 1) // one nonconstant feature.
{
all->l->learn(*ec);
all->l->finish_example(*all, *ec);
}
else if (ec->end_pass)
{
all->l->end_pass();
VW::finish_example(*all,ec);
}
else if (ec->tag.size() >= 4 && !strncmp((const char*) ec->tag.begin, "save", 4))
{//save state
string final_regressor_name = all->final_regressor_name;
if ((ec->tag).size() >= 6 && (ec->tag)[4] == '_')
final_regressor_name = string(ec->tag.begin+5, (ec->tag).size()-5);
if (!all->quiet)
cerr << "saving regressor to " << final_regressor_name << endl;
save_predictor(*all, final_regressor_name, 0);
VW::finish_example(*all,ec);
}
else
{
all->l->learn(*ec);
if(all->early_terminate)
{
all->p->done = true;
all->l->finish_example(*all, *ec);
return;
}
else
{
all->l->finish_example(*all, *ec);
}
}
}
else if (parser_done(all->p))
{
all->l->end_examples();
return;
}
}
}
}
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