ArgmaxTask Namespace Reference

Classes
struct	task_data

Functions
void	initialize (Search::search &sch, size_t &, options_i &options)
void	finish (Search::search &sch)
void	run (Search::search &sch, multi_ex &ec)

Variables
Search::search_task	task = {"argmax", run, initialize, finish, nullptr, nullptr}

Function Documentation

finish()

void ArgmaxTask::finish

(

Search::search &

sch

)

Definition at line 336 of file search_sequencetask.cc.

References Search::search::get_task_data().

{
  task_data* D = sch.get_task_data<task_data>();
  delete D;
}

initialize()

void ArgmaxTask::initialize	(	Search::search &	sch,
		size_t &	,
		options_i &	options
	)

Definition at line 315 of file search_sequencetask.cc.

References VW::config::option_group_definition::add(), add(), VW::config::options_i::add_and_parse(), Search::AUTO_CONDITION_FEATURES, Search::EXAMPLES_DONT_CHANGE, f, ArgmaxTask::task_data::false_negative_cost, VW::config::make_option(), ArgmaxTask::task_data::negative_weight, ArgmaxTask::task_data::predict_max, Search::search::set_options(), and Search::search::set_task_data().

{
  task_data* D = new task_data();

  option_group_definition new_options("argmax options");
  new_options.add(make_option("cost", D->false_negative_cost).default_value(10.0f).help("False Negative Cost"))
      .add(make_option("negative_weight", D->negative_weight)
               .default_value(1.f)
               .help("Relative weight of negative examples"))
      .add(make_option("max", D->predict_max).help("Disable structure: just predict the max"));
  options.add_and_parse(new_options);

  sch.set_task_data(D);

  if (D->predict_max)
    sch.set_options(Search::EXAMPLES_DONT_CHANGE);  // we don't do any internal example munging
  else
    sch.set_options(Search::AUTO_CONDITION_FEATURES |  // automatically add history features to our examples, please
        Search::EXAMPLES_DONT_CHANGE);                 // we don't do any internal example munging
}

run()

void ArgmaxTask::run	(	Search::search &	sch,
		multi_ex &	ec
	)

Definition at line 342 of file search_sequencetask.cc.

References ArgmaxTask::task_data::false_negative_cost, Search::search::get_task_data(), loss(), Search::search::loss(), ArgmaxTask::task_data::negative_weight, Search::search::output(), Search::search::predict(), and ArgmaxTask::task_data::predict_max.

{
  task_data& D = *sch.get_task_data<task_data>();
  uint32_t max_prediction = 1;
  uint32_t max_label = 1;

  for (size_t i = 0; i < ec.size(); i++) max_label = std::max(ec[i]->l.multi.label, max_label);

  for (ptag i = 0; i < ec.size(); i++)
  {
    // labels should be 1 or 2, and our output is MAX of all predicted values
    uint32_t oracle = D.predict_max ? max_label : ec[i]->l.multi.label;
    uint32_t prediction = sch.predict(*ec[i], i + 1, &oracle, 1, &i, "p");

    max_prediction = std::max(prediction, max_prediction);
  }
  float loss = 0.;
  if (max_label > max_prediction)
    loss = D.false_negative_cost / D.negative_weight;
  else if (max_prediction > max_label)
    loss = 1.;
  sch.loss(loss);

  if (sch.output().good())
    sch.output() << max_prediction;
}

Variable Documentation

task

Search::search_task ArgmaxTask::task = {"argmax", run, initialize, finish, nullptr, nullptr}

Definition at line 25 of file search_sequencetask.cc.