21 void reset_example(
example& ec);
26 static constexpr
int AUTOCONSTANT = 524267083;
31 : _poly_degree(poly_degree), _stride_shift(stride_shift)
76 template <
bool is_learn>
89 new_options.
add(
make_option(
"autolink", d).keep().help(
"create link function with polynomial d"));
95 auto autolink_reduction = scoped_calloc_or_throw<VW::autolink>(d, all.
weights.
stride_shift());
v_array< namespace_index > indices
void predict(E &ec, size_t i=0)
uint64_t stride_shift(const stagewise_poly &poly, uint64_t idx)
void push_back(feature_value v, feature_index i)
autolink(uint32_t d, uint32_t stride_shift)
void predict_or_learn(VW::autolink &b, LEARNER::single_learner &base, example &ec)
the core definition of a set of features.
base_learner * make_base(learner< T, E > &base)
virtual void add_and_parse(const option_group_definition &group)=0
std::array< features, NUM_NAMESPACES > feature_space
single_learner * as_singleline(learner< T, E > *l)
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)
void push_back(const T &new_ele)
virtual bool was_supplied(const std::string &key)=0
constexpr unsigned char autolink_namespace
option_group_definition & add(T &&op)
typed_option< T > make_option(std::string name, T &location)
void reset_example(example &ec)
void predict(LEARNER::single_learner &base, example &ec)
LEARNER::base_learner * setup_base(options_i &options, vw &all)
void predict(bfgs &b, base_learner &, example &ec)
static constexpr int AUTOCONSTANT
void learn(E &ec, size_t i=0)
void prepare_example(LEARNER::single_learner &base, example &ec)
void learn(LEARNER::single_learner &base, example &ec)
void learn(bfgs &b, base_learner &base, example &ec)
const uint32_t _poly_degree
LEARNER::base_learner * autolink_setup(options_i &options, vw &all)
const uint32_t _stride_shift