ftrl.h File Reference

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Functions
LEARNER::base_learner *	ftrl_setup (VW::config::options_i &options, vw &all)

Function Documentation

ftrl_setup()

LEARNER::base_learner* ftrl_setup	(	VW::config::options_i &	options,
		vw &	all
	)

Definition at line 335 of file ftrl.cc.

References VW::config::option_group_definition::add(), add(), VW::config::options_i::add_and_parse(), vw::audit, LEARNER::end_pass(), VW::config::options_i::get_typed_option(), vw::hash_inv, shared_data::holdout_best_loss, vw::holdout_set_off, LEARNER::init_learner(), learn_cb(), learn_pistol(), LEARNER::make_base(), VW::config::make_option(), vw::normalized_sum_norm_x, vw::quiet, save_load(), vw::sd, sensitivity(), parameters::stride_shift(), UINT64_ONE, VW::config::options_i::was_supplied(), and vw::weights.

Referenced by parse_reductions().

{
  auto b = scoped_calloc_or_throw<ftrl>();
  bool ftrl_option = false;
  bool pistol = false;
  bool coin = false;

  option_group_definition new_options("Follow the Regularized Leader");
  new_options.add(make_option("ftrl", ftrl_option).keep().help("FTRL: Follow the Proximal Regularized Leader"))
      .add(make_option("coin", coin).keep().help("Coin betting optimizer"))
      .add(make_option("pistol", pistol).keep().help("PiSTOL: Parameter-free STOchastic Learning"))
      .add(make_option("ftrl_alpha", b->ftrl_alpha).help("Learning rate for FTRL optimization"))
      .add(make_option("ftrl_beta", b->ftrl_beta).help("Learning rate for FTRL optimization"));
  options.add_and_parse(new_options);

  if (!ftrl_option && !pistol && !coin)
  {
    return nullptr;
  }

  // Defaults that are specific to the mode that was chosen.
  if (ftrl_option)
  {
    b->ftrl_alpha = options.was_supplied("ftrl_alpha") ? b->ftrl_alpha : 0.005f;
    b->ftrl_beta = options.was_supplied("ftrl_beta") ? b->ftrl_beta : 0.1f;
  }
  else if (pistol)
  {
    b->ftrl_alpha = options.was_supplied("ftrl_alpha") ? b->ftrl_alpha : 1.0f;
    b->ftrl_beta = options.was_supplied("ftrl_beta") ? b->ftrl_beta : 0.5f;
  }
  else if (coin)
  {
    b->ftrl_alpha = options.was_supplied("ftrl_alpha") ? b->ftrl_alpha : 4.0f;
    b->ftrl_beta = options.was_supplied("ftrl_beta") ? b->ftrl_beta : 1.0f;
  }

  b->all = &all;
  b->no_win_counter = 0;
  b->all->normalized_sum_norm_x = 0;
  b->total_weight = 0;

  void (*learn_ptr)(ftrl&, single_learner&, example&) = nullptr;

  std::string algorithm_name;
  if (ftrl_option)
  {
    algorithm_name = "Proximal-FTRL";
    if (all.audit)
      learn_ptr = learn_proximal<true>;
    else
      learn_ptr = learn_proximal<false>;
    all.weights.stride_shift(2);  // NOTE: for more parameter storage
    b->ftrl_size = 3;
  }
  else if (pistol)
  {
    algorithm_name = "PiSTOL";
    learn_ptr = learn_pistol;
    all.weights.stride_shift(2);  // NOTE: for more parameter storage
    b->ftrl_size = 4;
  }
  else if (coin)
  {
    algorithm_name = "Coin Betting";
    learn_ptr = learn_cb;
    all.weights.stride_shift(3);  // NOTE: for more parameter storage
    b->ftrl_size = 6;
  }

  b->data.ftrl_alpha = b->ftrl_alpha;
  b->data.ftrl_beta = b->ftrl_beta;
  b->data.l1_lambda = b->all->l1_lambda;
  b->data.l2_lambda = b->all->l2_lambda;

  if (!all.quiet)
  {
    std::cerr << "Enabling FTRL based optimization" << std::endl;
    std::cerr << "Algorithm used: " << algorithm_name << std::endl;
    std::cerr << "ftrl_alpha = " << b->ftrl_alpha << std::endl;
    std::cerr << "ftrl_beta = " << b->ftrl_beta << std::endl;
  }

  if (!all.holdout_set_off)
  {
    all.sd->holdout_best_loss = FLT_MAX;
    b->early_stop_thres = options.get_typed_option<size_t>("early_terminate").value();
  }

  learner<ftrl, example>* l;
  if (all.audit || all.hash_inv)
    l = &init_learner(b, learn_ptr, predict<true>, UINT64_ONE << all.weights.stride_shift());
  else
    l = &init_learner(b, learn_ptr, predict<false>, UINT64_ONE << all.weights.stride_shift());
  l->set_sensitivity(sensitivity);
  if (all.audit || all.hash_inv)
    l->set_multipredict(multipredict<true>);
  else
    l->set_multipredict(multipredict<false>);
  l->set_save_load(save_load);
  l->set_end_pass(end_pass);
  return make_base(*l);
}