lrq.h File Reference

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

Function Documentation

lrq_setup()

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

Definition at line 159 of file lrq.cc.

References VW::config::option_group_definition::add(), VW::config::options_i::add_and_parse(), LEARNER::as_singleline(), LEARNER::init_learner(), LEARNER::make_base(), VW::config::make_option(), vw::quiet, vw::random_seed, reset_seed(), LEARNER::learner< T, E >::set_end_pass(), setup_base(), spoof_hex_encoded_namespaces(), THROW, vw::trace_message, valid_int(), VW::config::options_i::was_supplied(), and vw::wpp.

Referenced by parse_reductions().

{
  auto lrq = scoped_calloc_or_throw<LRQstate>();
  std::vector<std::string> lrq_names;
  option_group_definition new_options("Low Rank Quadratics");
  new_options.add(make_option("lrq", lrq_names).keep().help("use low rank quadratic features"))
      .add(make_option("lrqdropout", lrq->dropout).keep().help("use dropout training for low rank quadratic features"));
  options.add_and_parse(new_options);

  if (!options.was_supplied("lrq"))
    return nullptr;

  uint32_t maxk = 0;
  lrq->all = &all;

  for (auto& lrq_name : lrq_names) lrq_name = spoof_hex_encoded_namespaces(lrq_name);

  new (&lrq->lrpairs) std::set<std::string>(lrq_names.begin(), lrq_names.end());

  lrq->initial_seed = lrq->seed = all.random_seed | 8675309;

  if (!all.quiet)
  {
    all.trace_message << "creating low rank quadratic features for pairs: ";
    if (lrq->dropout)
      all.trace_message << "(using dropout) ";
  }

  for (std::string const& i : lrq->lrpairs)
  {
    if (!all.quiet)
    {
      if ((i.length() < 3) || !valid_int(i.c_str() + 2))
        THROW("error, low-rank quadratic features must involve two sets and a rank.");

      all.trace_message << i << " ";
    }
    // TODO: colon-syntax

    unsigned int k = atoi(i.c_str() + 2);

    lrq->lrindices[(int)i[0]] = true;
    lrq->lrindices[(int)i[1]] = true;

    maxk = std::max(k, k);
  }

  if (!all.quiet)
    all.trace_message << std::endl;

  all.wpp = all.wpp * (uint64_t)(1 + maxk);
  learner<LRQstate, example>& l = init_learner(
      lrq, as_singleline(setup_base(options, all)), predict_or_learn<true>, predict_or_learn<false>, 1 + maxk);
  l.set_end_pass(reset_seed);

  // TODO: leaks memory ?
  return make_base(l);
}