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VW::cb_explore_adf::softmax Namespace Reference

Classes

struct  cb_explore_adf_softmax
 

Functions

LEARNER::base_learnersetup (VW::config::options_i &options, vw &all)
 

Function Documentation

◆ setup()

LEARNER::base_learner * VW::cb_explore_adf::softmax::setup ( VW::config::options_i options,
vw all 
)

Definition at line 52 of file cb_explore_adf_softmax.cc.

References prediction_type::action_probs, VW::config::option_group_definition::add(), VW::config::options_i::add_and_parse(), LEARNER::as_multiline(), label_type::cb, CB::cb_label, ACTION_SCORE::delete_action_scores(), vw::delete_prediction, f, finish_multiline_example(), LEARNER::init_learner(), VW::config::options_i::insert(), vw::label_type, learn(), parser::lp, LEARNER::make_base(), VW::config::make_option(), vw::p, predict(), setup_base(), vw_slim::softmax, and VW::config::options_i::was_supplied().

Referenced by parse_reductions().

53 {
54  using config::make_option;
55  bool cb_explore_adf_option = false;
56  bool softmax = false;
57  float epsilon = 0.;
58  float lambda = 0.;
59  config::option_group_definition new_options("Contextual Bandit Exploration with Action Dependent Features");
60  new_options
61  .add(make_option("cb_explore_adf", cb_explore_adf_option)
62  .keep()
63  .help("Online explore-exploit for a contextual bandit problem with multiline action dependent features"))
64  .add(make_option("epsilon", epsilon).keep().help("epsilon-greedy exploration"))
65  .add(make_option("softmax", softmax).keep().help("softmax exploration"))
66  .add(make_option("lambda", lambda).keep().default_value(1.f).help("parameter for softmax"));
67  options.add_and_parse(new_options);
68 
69  if (!cb_explore_adf_option || !softmax)
70  return nullptr;
71 
72  if (lambda < 0) // Lambda should always be positive because we are using a cost basis.
73  lambda = -lambda;
74 
75  // Ensure serialization of cb_adf in all cases.
76  if (!options.was_supplied("cb_adf"))
77  {
78  options.insert("cb_adf", "");
79  }
80 
82 
83  // Set explore_type
84  size_t problem_multiplier = 1;
85 
86  LEARNER::multi_learner* base = as_multiline(setup_base(options, all));
87  all.p->lp = CB::cb_label;
89 
90  using explore_type = cb_explore_adf_base<cb_explore_adf_softmax>;
91  auto data = scoped_calloc_or_throw<explore_type>(epsilon, lambda);
94 
95  l.set_finish_example(explore_type::finish_multiline_example);
96  return make_base(l);
97 }
void(* delete_prediction)(void *)
Definition: global_data.h:485
void finish_multiline_example(vw &all, cbify &, multi_ex &ec_seq)
Definition: cbify.cc:373
label_type::label_type_t label_type
Definition: global_data.h:550
base_learner * make_base(learner< T, E > &base)
Definition: learner.h:462
virtual void add_and_parse(const option_group_definition &group)=0
parser * p
Definition: global_data.h:377
learner< T, E > & init_learner(free_ptr< T > &dat, L *base, void(*learn)(T &, L &, E &), void(*predict)(T &, L &, E &), size_t ws, prediction_type::prediction_type_t pred_type)
Definition: learner.h:369
void delete_action_scores(void *v)
Definition: action_score.cc:29
virtual bool was_supplied(const std::string &key)=0
virtual void insert(const std::string &key, const std::string &value)=0
label_parser cb_label
Definition: cb.cc:167
typed_option< T > make_option(std::string name, T &location)
Definition: options.h:80
LEARNER::base_learner * setup_base(options_i &options, vw &all)
Definition: parse_args.cc:1222
void predict(bfgs &b, base_learner &, example &ec)
Definition: bfgs.cc:956
void learn(bfgs &b, base_learner &base, example &ec)
Definition: bfgs.cc:965
float f
Definition: cache.cc:40
multi_learner * as_multiline(learner< T, E > *l)
Definition: learner.h:468
label_parser lp
Definition: parser.h:102