CB_ADF Namespace Reference

Classes
struct	cb_adf

Functions
CB::cb_class	get_observed_cost (multi_ex &examples)
example *	test_adf_sequence (multi_ex &ec_seq)
void	global_print_newline (const v_array< int > &final_prediction_sink)
void	output_example (vw &all, cb_adf &c, example &ec, multi_ex *ec_seq)
void	output_rank_example (vw &all, cb_adf &c, example &ec, multi_ex *ec_seq)
void	output_example_seq (vw &all, cb_adf &data, multi_ex &ec_seq)
void	finish_multiline_example (vw &all, cb_adf &data, multi_ex &ec_seq)
void	save_load (cb_adf &c, io_buf &model_file, bool read, bool text)
void	learn (cb_adf &c, multi_learner &base, multi_ex &ec_seq)
void	predict (cb_adf &c, multi_learner &base, multi_ex &ec_seq)

Function Documentation

finish_multiline_example()

void CB_ADF::finish_multiline_example	(	vw &	all,
		cb_adf &	data,
		multi_ex &	ec_seq
	)

Definition at line 451 of file cb_adf.cc.

References vw::final_prediction_sink, VW::finish_example(), global_print_newline(), and output_example_seq().

Referenced by cb_adf_setup().

{
  if (!ec_seq.empty())
  {
    output_example_seq(all, data, ec_seq);
    global_print_newline(all.final_prediction_sink);
  }
  VW::finish_example(all, ec_seq);
}

get_observed_cost()

CB::cb_class CB_ADF::get_observed_cost

(

multi_ex &

examples

)

Definition at line 99 of file cb_adf.cc.

References CB::cb_class::action, CB::label::costs, and CB::cb_class::probability.

Referenced by CB_ADF::cb_adf::do_actual_learning(), EXPLORE_EVAL::do_actual_learning(), VW::cb_explore_adf::cb_explore_adf_base< ExploreType >::learn(), CB_ALGS::learn_eval(), CB_EXPLORE::output_example(), VW::cb_explore_adf::cb_explore_adf_base< ExploreType >::predict(), CB_ALGS::predict_or_learn(), CB_EXPLORE::predict_or_learn_cover(), and VW::cb_explore_adf::cover::cb_explore_adf_cover::predict_or_learn_impl().

{
  CB::label ld;
  ld.costs = v_init<cb_class>();
  int index = -1;
  CB::cb_class known_cost;

  size_t i = 0;
  for (example*& ec : examples)
  {
    if (ec->l.cb.costs.size() == 1 && ec->l.cb.costs[0].cost != FLT_MAX && ec->l.cb.costs[0].probability > 0)
    {
      ld = ec->l.cb;
      index = (int)i;
    }
    ++i;
  }

  // handle -1 case.
  if (index == -1)
  {
    known_cost.probability = -1;
    return known_cost;
    // std::cerr << "None of the examples has known cost. Exiting." << std::endl;
    // throw exception();
  }

  known_cost = ld.costs[0];
  known_cost.action = index;
  return known_cost;
}

global_print_newline()

void CB_ADF::global_print_newline

(

const v_array< int > &

final_prediction_sink

)

Definition at line 342 of file cb_adf.cc.

References f, and io_buf::write_file_or_socket().

Referenced by VW::cb_explore_adf::cb_explore_adf_base< ExploreType >::finish_multiline_example(), EXPLORE_EVAL::finish_multiline_example(), finish_multiline_example(), and CCB::finish_multiline_example().

{
  char temp[1];
  temp[0] = '\n';
  for (auto f : final_prediction_sink)
  {
    ssize_t t;
    t = io_buf::write_file_or_socket(f, temp, 1);
    if (t != 1)
      std::cerr << "write error: " << strerror(errno) << std::endl;
  }
}

learn()

void CB_ADF::learn	(	cb_adf &	c,
		multi_learner &	base,
		multi_ex &	ec_seq
	)

Definition at line 475 of file cb_adf.cc.

References CB_ADF::cb_adf::do_actual_learning().

Referenced by cb_adf_setup().

{ c.do_actual_learning<true>(base, ec_seq); }

output_example()

void CB_ADF::output_example	(	vw &	all,
		cb_adf &	c,
		example &	ec,
		multi_ex *	ec_seq
	)

Definition at line 379 of file cb_adf.cc.

References polyprediction::a_s, polylabel::cb, CB::label::costs, LEARNER::example_is_newline_not_header(), vw::final_prediction_sink, example::l, example::pred, vw::print, vw::print_text, CB::print_update(), vw::raw_prediction, v_array< T >::size(), example::tag, and CB_ADF::cb_adf::update_statistics().

Referenced by output_example_seq().

{
  if (example_is_newline_not_header(ec))
    return;

  bool labeled_example = c.update_statistics(ec, ec_seq);

  uint32_t action = ec.pred.a_s[0].action;
  for (int sink : all.final_prediction_sink) all.print(sink, (float)action, 0, ec.tag);

  if (all.raw_prediction > 0)
  {
    std::string outputString;
    std::stringstream outputStringStream(outputString);
    v_array<CB::cb_class> costs = ec.l.cb.costs;

    for (size_t i = 0; i < costs.size(); i++)
    {
      if (i > 0)
        outputStringStream << ' ';
      outputStringStream << costs[i].action << ':' << costs[i].partial_prediction;
    }
    all.print_text(all.raw_prediction, outputStringStream.str(), ec.tag);
  }

  CB::print_update(all, !labeled_example, ec, ec_seq, true);
}

output_example_seq()

void CB_ADF::output_example_seq	(	vw &	all,
		cb_adf &	data,
		multi_ex &	ec_seq
	)

Definition at line 435 of file cb_adf.cc.

References CB_ADF::cb_adf::get_rank_all(), output_example(), output_rank_example(), vw::print_text, and vw::raw_prediction.

{
  if (!ec_seq.empty())
  {
    if (data.get_rank_all())
      output_rank_example(all, data, **(ec_seq.begin()), &(ec_seq));
    else
    {
      output_example(all, data, **(ec_seq.begin()), &(ec_seq));

      if (all.raw_prediction > 0)
        all.print_text(all.raw_prediction, "", ec_seq[0]->tag);
    }
  }
}

output_rank_example()

void CB_ADF::output_rank_example	(	vw &	all,
		cb_adf &	c,
		example &	ec,
		multi_ex *	ec_seq
	)

Definition at line 407 of file cb_adf.cc.

References polyprediction::a_s, polylabel::cb, CB::label::costs, LEARNER::example_is_newline_not_header(), vw::final_prediction_sink, example::l, example::pred, ACTION_SCORE::print_action_score(), vw::print_text, CB::print_update(), vw::raw_prediction, v_array< T >::size(), example::tag, and CB_ADF::cb_adf::update_statistics().

Referenced by output_example_seq().

{
  label& ld = ec.l.cb;
  v_array<CB::cb_class> costs = ld.costs;

  if (example_is_newline_not_header(ec))
    return;

  bool labeled_example = c.update_statistics(ec, ec_seq);

  for (int sink : all.final_prediction_sink) print_action_score(sink, ec.pred.a_s, ec.tag);

  if (all.raw_prediction > 0)
  {
    std::string outputString;
    std::stringstream outputStringStream(outputString);
    for (size_t i = 0; i < costs.size(); i++)
    {
      if (i > 0)
        outputStringStream << ' ';
      outputStringStream << costs[i].action << ':' << costs[i].partial_prediction;
    }
    all.print_text(all.raw_prediction, outputStringStream.str(), ec.tag);
  }

  CB::print_update(all, !labeled_example, ec, ec_seq, true);
}

predict()

void CB_ADF::predict	(	cb_adf &	c,
		multi_learner &	base,
		multi_ex &	ec_seq
	)

Definition at line 477 of file cb_adf.cc.

References CB_ADF::cb_adf::do_actual_learning().

Referenced by cb_adf_setup(), and CB_ADF::cb_adf::learn_MTR().

{ c.do_actual_learning<false>(base, ec_seq); }

save_load()

void CB_ADF::save_load	(	cb_adf &	c,
		io_buf &	model_file,
		bool	read,
		bool	text
	)

Definition at line 461 of file cb_adf.cc.

References GEN_CS::cb_to_cs_adf::action_sum, bin_text_read_write_fixed(), GEN_CS::cb_to_cs_adf::event_sum, CB_ADF::cb_adf::get_gen_cs(), CB_ADF::cb_adf::get_model_file_ver(), and VERSION_FILE_WITH_CB_ADF_SAVE.

Referenced by cb_adf_setup().

{
  if (c.get_model_file_ver() != nullptr && *c.get_model_file_ver() < VERSION_FILE_WITH_CB_ADF_SAVE)
    return;
  std::stringstream msg;
  msg << "event_sum " << c.get_gen_cs().event_sum << "\n";
  bin_text_read_write_fixed(
      model_file, (char*)&c.get_gen_cs().event_sum, sizeof(c.get_gen_cs().event_sum), "", read, msg, text);

  msg << "action_sum " << c.get_gen_cs().action_sum << "\n";
  bin_text_read_write_fixed(
      model_file, (char*)&c.get_gen_cs().action_sum, sizeof(c.get_gen_cs().action_sum), "", read, msg, text);
}

test_adf_sequence()

example * CB_ADF::test_adf_sequence

(

multi_ex &

ec_seq

)

Definition at line 268 of file cb_adf.cc.

References THROW.

Referenced by CB_ADF::cb_adf::do_actual_learning(), EXPLORE_EVAL::do_actual_learning(), VW::cb_explore_adf::cb_explore_adf_base< ExploreType >::learn(), and VW::cb_explore_adf::cb_explore_adf_base< ExploreType >::predict().

{
  if (ec_seq.empty())
    THROW("cb_adf: At least one action must be provided for an example to be valid.");

  uint32_t count = 0;
  example* ret = nullptr;
  for (auto* ec : ec_seq)
  {
    // Check if there is more than one cost for this example.
    if (ec->l.cb.costs.size() > 1)
      THROW("cb_adf: badly formatted example, only one cost can be known.");

    // Check whether the cost was initialized to a value.
    if (ec->l.cb.costs.size() == 1 && ec->l.cb.costs[0].cost != FLT_MAX)
    {
      ret = ec;
      count += 1;
      if (count > 1)
        THROW("cb_adf: badly formatted example, only one line can have a cost");
    }
  }

  return ret;
}