CB_ALGS Namespace Reference

Classes
struct	cb

Functions
bool	know_all_cost_example (CB::label &ld)
template<bool is_learn>
void	predict_or_learn (cb &data, single_learner &base, example &ec)
void	predict_eval (cb &, single_learner &, example &)
void	learn_eval (cb &data, single_learner &, example &ec)
void	output_example (vw &all, cb &data, example &ec, CB::label &ld)
void	finish_example (vw &all, cb &c, example &ec)
void	eval_finish_example (vw &all, cb &c, example &ec)
template<bool is_learn>
float	get_cost_pred (LEARNER::single_learner *scorer, CB::cb_class *known_cost, example &ec, uint32_t index, uint32_t base)
float	get_cost_estimate (CB::cb_class *observation, uint32_t action, float offset=0.)
float	get_cost_estimate (CB::cb_class *observation, COST_SENSITIVE::label &scores, uint32_t action)
float	get_cost_estimate (ACTION_SCORE::action_score &a_s, float cost, uint32_t action, float offset=0.)
bool	example_is_newline_not_header (example const &ec)

Function Documentation

eval_finish_example()

void CB_ALGS::eval_finish_example	(	vw &	all,
		cb &	c,
		example &	ec
	)

Definition at line 125 of file cb_algs.cc.

References polylabel::cb_eval, CB_EVAL::label::event, VW::finish_example(), example::l, and output_example().

Referenced by cb_algs_setup().

{
  output_example(all, c, ec, ec.l.cb_eval.event);
  VW::finish_example(all, ec);
}

example_is_newline_not_header()

bool CB_ALGS::example_is_newline_not_header ( example const &  ec )

inline

Definition at line 80 of file cb_algs.h.

References CB::ec_is_example_header(), and example_is_newline().

Referenced by copy_example_to_adf(), and GEN_CS::gen_cs_example_dr().

{
  return (example_is_newline(ec) && !CB::ec_is_example_header(ec));
}

finish_example()

void CB_ALGS::finish_example	(	vw &	all,
		cb &	c,
		example &	ec
	)

Definition at line 119 of file cb_algs.cc.

References polylabel::cb, VW::finish_example(), example::l, and output_example().

Referenced by cb_algs_setup().

{
  output_example(all, c, ec, ec.l.cb);
  VW::finish_example(all, ec);
}

get_cost_estimate() [1/3]

float CB_ALGS::get_cost_estimate ( CB::cb_class *  observation, uint32_t  action, float  offset = 0.  )

inline

Definition at line 58 of file cb_algs.h.

References CB::cb_class::action, CB::cb_class::cost, and CB::cb_class::probability.

Referenced by MWT::finish_example(), get_cost_estimate(), EXPLORE_EVAL::output_example(), VW::cb_explore_adf::cb_explore_adf_base< ExploreType >::output_example(), output_example(), CB_EXPLORE::output_example(), CCB::output_example(), MWT::predict_or_learn(), and CB_ADF::cb_adf::update_statistics().

{
  if (action == observation->action)
    return (observation->cost - offset) / observation->probability;
  return 0.;
}

get_cost_estimate() [2/3]

float CB_ALGS::get_cost_estimate ( CB::cb_class *  observation, COST_SENSITIVE::label &  scores, uint32_t  action  )

inline

Definition at line 65 of file cb_algs.h.

References COST_SENSITIVE::label::costs, and get_cost_estimate().

{
  for (auto& cl : scores.costs)
    if (cl.class_index == action)
      return get_cost_estimate(observation, action, cl.x) + cl.x;
  return get_cost_estimate(observation, action);
}

get_cost_estimate() [3/3]

float CB_ALGS::get_cost_estimate ( ACTION_SCORE::action_score &  a_s, float  cost, uint32_t  action, float  offset = 0.  )

inline

Definition at line 73 of file cb_algs.h.

References ACTION_SCORE::action_score::action, and ACTION_SCORE::action_score::score.

{
  if (action == a_s.action)
    return (cost - offset) / a_s.score;
  return 0.;
}

get_cost_pred()

template<bool is_learn>

float CB_ALGS::get_cost_pred	(	LEARNER::single_learner *	scorer,
		CB::cb_class *	known_cost,
		example &	ec,
		uint32_t	index,
		uint32_t	base
	)

Definition at line 22 of file cb_algs.h.

References CB::cb_class::action, BASELINE::baseline_enabled(), polylabel::cb, CB::cb_class::cost, label_data::initial, example::l, label_data::label, LEARNER::learner< T, E >::learn(), example::pred, LEARNER::learner< T, E >::predict(), CB::cb_class::probability, BASELINE::reset_baseline_disabled(), polyprediction::scalar, BASELINE::set_baseline_enabled(), polylabel::simple, and example::weight.

{
  CB::label ld = ec.l.cb;

  label_data simple_temp;
  simple_temp.initial = 0.;
  if (known_cost != nullptr && index == known_cost->action)
    simple_temp.label = known_cost->cost;
  else
    simple_temp.label = FLT_MAX;

  const bool baseline_enabled_old = BASELINE::baseline_enabled(&ec);
  BASELINE::set_baseline_enabled(&ec);
  ec.l.simple = simple_temp;
  polyprediction p = ec.pred;
  if (is_learn && known_cost != nullptr && index == known_cost->action)
  {
    float old_weight = ec.weight;
    ec.weight /= known_cost->probability;
    scorer->learn(ec, index - 1 + base);
    ec.weight = old_weight;
  }
  else
    scorer->predict(ec, index - 1 + base);

  if (!baseline_enabled_old)
    BASELINE::reset_baseline_disabled(&ec);
  float pred = ec.pred.scalar;
  ec.pred = p;

  ec.l.cb = ld;

  return pred;
}

know_all_cost_example()

bool CB_ALGS::know_all_cost_example

(

CB::label &

ld

)

Definition at line 33 of file cb_algs.cc.

References CB::label::costs.

{
  if (ld.costs.size() <= 1)  // this means we specified an example where all actions are possible but only specified the
                             // cost for the observed action
    return false;

  // if we specified more than 1 action for this example, i.e. either we have a limited set of possible actions, or all
  // actions are specified than check if all actions have a specified cost
  for (auto& cl : ld.costs)
    if (cl.cost == FLT_MAX)
      return false;

  return true;
}

learn_eval()

void CB_ALGS::learn_eval	(	cb &	data,
		single_learner &	,
		example &	ec
	)

Definition at line 77 of file cb_algs.cc.

References c, CB_ALGS::cb::cb_cs_ld, polylabel::cb_eval, CB_ALGS::cb::cbcs, CB::label::costs, COST_SENSITIVE::label::costs, CB_EVAL::label::event, CB_ADF::get_observed_cost(), GEN_CS::cb_to_cs::known_cost, and example::l.

Referenced by cb_algs_setup().

{
  CB_EVAL::label ld = ec.l.cb_eval;

  cb_to_cs& c = data.cbcs;
  c.known_cost = get_observed_cost(ld.event);
  gen_cs_example<true>(c, ec, ld.event, data.cb_cs_ld);

  for (size_t i = 0; i < ld.event.costs.size(); i++)
    ld.event.costs[i].partial_prediction = data.cb_cs_ld.costs[i].partial_prediction;

  ec.pred.multiclass = ec.l.cb_eval.action;
}

output_example()

void CB_ALGS::output_example	(	vw &	all,
		cb &	data,
		example &	ec,
		CB::label &	ld
	)

Definition at line 91 of file cb_algs.cc.

References CB::cb_class::action, c, CB::cb_label, CB_ALGS::cb::cbcs, CB::label::costs, vw::final_prediction_sink, get_cost_estimate(), GEN_CS::cb_to_cs::known_cost, loss(), polyprediction::multiclass, example::num_features, CB::cb_class::partial_prediction, example::pred, GEN_CS::cb_to_cs::pred_scores, vw::print, vw::print_text, CB::print_update(), vw::raw_prediction, vw::sd, example::tag, label_parser::test_label, test_label(), example::test_only, and shared_data::update().

Referenced by eval_finish_example(), and finish_example().

{
  float loss = 0.;

  cb_to_cs& c = data.cbcs;
  if (!CB::cb_label.test_label(&ld))
    loss = get_cost_estimate(c.known_cost, c.pred_scores, ec.pred.multiclass);

  all.sd->update(ec.test_only, !CB::cb_label.test_label(&ld), loss, 1.f, ec.num_features);

  for (int sink : all.final_prediction_sink) all.print(sink, (float)ec.pred.multiclass, 0, ec.tag);

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

  print_update(all, CB::cb_label.test_label(&ld), ec, nullptr, false);
}

predict_eval()

void CB_ALGS::predict_eval	(	cb &	,
		single_learner &	,
		example &
	)

Definition at line 75 of file cb_algs.cc.

References THROW.

Referenced by cb_algs_setup().

{ THROW("can not use a test label for evaluation"); }

predict_or_learn()

template<bool is_learn>

void CB_ALGS::predict_or_learn	(	cb &	data,
		single_learner &	base,
		example &	ec
	)

Definition at line 49 of file cb_algs.cc.

References CB::cb_class::action, c, polylabel::cb, CB_ALGS::cb::cb_cs_ld, CB_TYPE_DM, CB_ALGS::cb::cbcs, COST_SENSITIVE::label::costs, CB_ADF::get_observed_cost(), GEN_CS::cb_to_cs::known_cost, example::l, LEARNER::learner< T, E >::learn(), GEN_CS::cb_to_cs::num_actions, and LEARNER::learner< T, E >::predict().

{
  CB::label ld = ec.l.cb;
  cb_to_cs& c = data.cbcs;
  c.known_cost = get_observed_cost(ld);
  if (c.known_cost != nullptr && (c.known_cost->action < 1 || c.known_cost->action > c.num_actions))
    std::cerr << "invalid action: " << c.known_cost->action << std::endl;

  // generate a cost-sensitive example to update classifiers
  gen_cs_example<is_learn>(c, ec, ld, data.cb_cs_ld);

  if (c.cb_type != CB_TYPE_DM)
  {
    ec.l.cs = data.cb_cs_ld;

    if (is_learn)
      base.learn(ec);
    else
      base.predict(ec);

    for (size_t i = 0; i < ld.costs.size(); i++)
      ld.costs[i].partial_prediction = data.cb_cs_ld.costs[i].partial_prediction;
    ec.l.cb = ld;
  }
}