VW::LEARNER Namespace Reference

Contains the VW::LEARNER::learner object and utilities for interacting with it. More...

Classes
struct	base_learner_builder
struct	common_learner_builder
struct	finish_example_data
struct	func_data
struct	learn_data
struct	learner
	Defines the interface for a learning algorithm. More...
struct	reduction_learner_builder
struct	reduction_no_data_learner_builder
struct	save_load_data
struct	save_metric_data
struct	sensitivity_data

Typedefs
using	base_learner = learner< char, char >
	Used to type erase the object and pass around common type. More...
using	single_learner = learner< char, example >
	Used for reductions that process single example objects at at time. It type erases the specific reduction object type. More...
using	multi_learner = learner< char, multi_ex >
	Used for multiline examples where there are several example objects required to describe the overall example. It type erases the specific reduction object type. More...

Functions
func_data	tuple_dbf (void *data, base_learner *base, void(*func)(void *))
void	generic_driver (VW::workspace &all)
void	generic_driver (const std::vector< VW::workspace *> &alls)
void	generic_driver_onethread (VW::workspace &all)
void	noop_save_load (void *, io_buf &, bool, bool)
void	noop_persist_metrics (void *, metric_sink &)
void	noop (void *)
float	noop_sensitivity (void *, base_learner &, example &)
float	recur_sensitivity (void *, base_learner &, example &)
void	debug_increment_depth (example &ex)
void	debug_increment_depth (multi_ex &ec_seq)
void	debug_decrement_depth (example &ex)
void	debug_decrement_depth (multi_ex &ec_seq)
void	increment_offset (example &ex, const size_t increment, const size_t i)
void	increment_offset (multi_ex &ec_seq, const size_t increment, const size_t i)
void	decrement_offset (example &ex, const size_t increment, const size_t i)
void	decrement_offset (multi_ex &ec_seq, const size_t increment, const size_t i)
bool	ec_is_example_header (example const &ec, label_type_t label_type)
template<class T , class E >
base_learner *	make_base (learner< T, E > &base)
template<class T , class E >
multi_learner *	as_multiline (learner< T, E > *l)
template<class T , class E >
single_learner *	as_singleline (learner< T, E > *l)
template<bool is_learn>
void	multiline_learn_or_predict (multi_learner &base, multi_ex &examples, const uint64_t offset, const uint32_t id=0)
float	noop_sensitivity_base (void *, example &)
template<class DataT , class ExampleT , class BaseLearnerT >
VW_WARNING_STATE_POP reduction_learner_builder< DataT, ExampleT, BaseLearnerT >	make_reduction_learner (std::unique_ptr< DataT > &&data, BaseLearnerT *base, void(*learn_fn)(DataT &, BaseLearnerT &, ExampleT &), void(*predict_fn)(DataT &, BaseLearnerT &, ExampleT &), const std::string &name)
template<class ExampleT , class BaseLearnerT >
reduction_no_data_learner_builder< ExampleT, BaseLearnerT >	make_no_data_reduction_learner (BaseLearnerT *base, void(*learn_fn)(char &, BaseLearnerT &, ExampleT &), void(*predict_fn)(char &, BaseLearnerT &, ExampleT &), const std::string &name)
template<class DataT , class ExampleT >
base_learner_builder< DataT, ExampleT >	make_base_learner (std::unique_ptr< DataT > &&data, void(*learn_fn)(DataT &, base_learner &, ExampleT &), void(*predict_fn)(DataT &, base_learner &, ExampleT &), const std::string &name, prediction_type_t out_pred_type, label_type_t in_label_type)
template<class ExampleT >
base_learner_builder< char, ExampleT >	make_no_data_base_learner (void(*learn_fn)(char &, base_learner &, ExampleT &), void(*predict_fn)(char &, base_learner &, ExampleT &), const std::string &name, prediction_type_t out_pred_type, label_type_t in_label_type)

Detailed Description

Contains the VW::LEARNER::learner object and utilities for interacting with it.

Typedef Documentation

base_learner

typedef learner< char, char > VW::LEARNER::base_learner

Used to type erase the object and pass around common type.

multi_learner

typedef learner< char, multi_ex > VW::LEARNER::multi_learner

Used for multiline examples where there are several example objects required to describe the overall example. It type erases the specific reduction object type.

single_learner

typedef learner< char, example > VW::LEARNER::single_learner

Used for reductions that process single example objects at at time. It type erases the specific reduction object type.

Function Documentation

as_multiline()

template<class T , class E >

multi_learner* VW::LEARNER::as_multiline

(

learner< T, E > *

l

)

as_singleline()

template<class T , class E >

single_learner* VW::LEARNER::as_singleline

(

learner< T, E > *

l

)

debug_decrement_depth() [1/2]

void VW::LEARNER::debug_decrement_depth ( example &  ex )

inline

debug_decrement_depth() [2/2]

void VW::LEARNER::debug_decrement_depth ( multi_ex &  ec_seq )

inline

debug_increment_depth() [1/2]

void VW::LEARNER::debug_increment_depth ( example &  ex )

inline

debug_increment_depth() [2/2]

void VW::LEARNER::debug_increment_depth ( multi_ex &  ec_seq )

inline

decrement_offset() [1/2]

void VW::LEARNER::decrement_offset ( example &  ex, const size_t  increment, const size_t  i  )

inline

decrement_offset() [2/2]

void VW::LEARNER::decrement_offset ( multi_ex &  ec_seq, const size_t  increment, const size_t  i  )

inline

ec_is_example_header()

bool VW::LEARNER::ec_is_example_header ( example const &  ec, label_type_t  label_type  )

inline

generic_driver() [1/2]

void VW::LEARNER::generic_driver

(

VW::workspace &

all

)

generic_driver() [2/2]

void VW::LEARNER::generic_driver

(

const std::vector< VW::workspace *> &

alls

)

generic_driver_onethread()

void VW::LEARNER::generic_driver_onethread

(

VW::workspace &

all

)

increment_offset() [1/2]

void VW::LEARNER::increment_offset ( example &  ex, const size_t  increment, const size_t  i  )

inline

increment_offset() [2/2]

void VW::LEARNER::increment_offset ( multi_ex &  ec_seq, const size_t  increment, const size_t  i  )

inline

make_base()

template<class T , class E >

base_learner* VW::LEARNER::make_base

(

learner< T, E > &

base

)

make_base_learner()

template<class DataT , class ExampleT >

base_learner_builder<DataT, ExampleT> VW::LEARNER::make_base_learner	(	std::unique_ptr< DataT > &&	data,
		void(*)(DataT &, base_learner &, ExampleT &)	learn_fn,
		void(*)(DataT &, base_learner &, ExampleT &)	predict_fn,
		const std::string &	name,
		prediction_type_t	out_pred_type,
		label_type_t	in_label_type
	)

make_no_data_base_learner()

template<class ExampleT >

base_learner_builder<char, ExampleT> VW::LEARNER::make_no_data_base_learner	(	void(*)(char &, base_learner &, ExampleT &)	learn_fn,
		void(*)(char &, base_learner &, ExampleT &)	predict_fn,
		const std::string &	name,
		prediction_type_t	out_pred_type,
		label_type_t	in_label_type
	)

make_no_data_reduction_learner()

template<class ExampleT , class BaseLearnerT >

reduction_no_data_learner_builder<ExampleT, BaseLearnerT> VW::LEARNER::make_no_data_reduction_learner	(	BaseLearnerT *	base,
		void(*)(char &, BaseLearnerT &, ExampleT &)	learn_fn,
		void(*)(char &, BaseLearnerT &, ExampleT &)	predict_fn,
		const std::string &	name
	)

make_reduction_learner()

template<class DataT , class ExampleT , class BaseLearnerT >

VW_WARNING_STATE_POP reduction_learner_builder<DataT, ExampleT, BaseLearnerT> VW::LEARNER::make_reduction_learner	(	std::unique_ptr< DataT > &&	data,
		BaseLearnerT *	base,
		void(*)(DataT &, BaseLearnerT &, ExampleT &)	learn_fn,
		void(*)(DataT &, BaseLearnerT &, ExampleT &)	predict_fn,
		const std::string &	name
	)

multiline_learn_or_predict()

template<bool is_learn>

void VW::LEARNER::multiline_learn_or_predict	(	multi_learner &	base,
		multi_ex &	examples,
		const uint64_t	offset,
		const uint32_t	id = 0
	)

noop()

void VW::LEARNER::noop ( void *  )

inline

noop_persist_metrics()

void VW::LEARNER::noop_persist_metrics ( void *  , metric_sink &    )

inline

noop_save_load()

void VW::LEARNER::noop_save_load ( void *  , io_buf &  , bool  , bool    )

inline

noop_sensitivity()

float VW::LEARNER::noop_sensitivity ( void *  , base_learner &  , example &    )

inline

noop_sensitivity_base()

float VW::LEARNER::noop_sensitivity_base ( void *  , example &    )

inline

recur_sensitivity()

float VW::LEARNER::recur_sensitivity	(	void *	,
		base_learner &	,
		example &
	)

tuple_dbf()

func_data VW::LEARNER::tuple_dbf ( void *  data, base_learner *  base, void(*)(void *)  func  )

inline