vw Struct Reference

#include <global_data.h>

Public Member Functions
void	learn (example &)
void	learn (multi_ex &)
void	predict (example &)
void	predict (multi_ex &)
void	finish_example (example &)
void	finish_example (multi_ex &)
size_t	length ()
	vw ()
	~vw ()
std::shared_ptr< rand_state >	get_random_state ()
	vw (const vw &)=delete
vw &	operator= (const vw &)=delete
	vw (const vw &&)=delete
vw &	operator= (const vw &&)=delete

Public Attributes
shared_data *	sd
parser *	example_parser
std::thread	parse_thread
AllReduceType	all_reduce_type
AllReduce *	all_reduce
bool	chain_hash_json = false
VW::LEARNER::base_learner *	l
VW::LEARNER::single_learner *	scorer
VW::LEARNER::base_learner *	cost_sensitive
void(*	set_minmax )(shared_data *sd, float label)
uint64_t	current_pass
uint32_t	num_bits
bool	default_bits
uint32_t	hash_seed
std::string	data_filename
bool	daemon
size_t	num_children
bool	save_per_pass
float	initial_weight
float	initial_constant
bool	bfgs
bool	hessian_on
bool	save_resume
bool	preserve_performance_counters
std::string	id
VW::version_struct	model_file_ver
double	normalized_sum_norm_x
bool	vw_is_main = false
vw_ostream	trace_message
bool	should_delete_options = false
VW::config::options_i *	options
void *	searchstr
uint32_t	wpp
std::unique_ptr< VW::io::writer >	stdout_adapter
std::vector< std::string >	initial_regressors
std::string	feature_mask
std::string	per_feature_regularizer_input
std::string	per_feature_regularizer_output
std::string	per_feature_regularizer_text
float	l1_lambda
float	l2_lambda
bool	no_bias
float	power_t
int	reg_mode
size_t	pass_length
size_t	numpasses
size_t	passes_complete
uint64_t	parse_mask
bool	permutations
std::vector< std::vector< namespace_index > >	interactions
bool	ignore_some
std::array< bool, NUM_NAMESPACES >	ignore
bool	ignore_some_linear
std::array< bool, NUM_NAMESPACES >	ignore_linear
bool	redefine_some
std::array< unsigned char, NUM_NAMESPACES >	redefine
std::unique_ptr< VW::kskip_ngram_transformer >	skip_gram_transformer
std::vector< std::string >	limit_strings
std::array< uint32_t, NUM_NAMESPACES >	limit
std::array< uint64_t, NUM_NAMESPACES >	affix_features
std::array< bool, NUM_NAMESPACES >	spelling_features
std::vector< std::string >	dictionary_path
std::vector< dictionary_info >	loaded_dictionaries
std::array< std::vector< std::shared_ptr< feature_dict > >, NUM_NAMESPACES >	namespace_dictionaries {}
void(*	delete_prediction )(void *)
vw_logger	logger
bool	audit
bool	training
bool	active
bool	invariant_updates
uint64_t	random_seed
bool	random_weights
bool	random_positive_weights
bool	normal_weights
bool	tnormal_weights
bool	add_constant
bool	nonormalize
bool	do_reset_source
bool	holdout_set_off
bool	early_terminate
uint32_t	holdout_period
uint32_t	holdout_after
size_t	check_holdout_every_n_passes
size_t	normalized_idx
uint32_t	lda
std::string	text_regressor_name
std::string	inv_hash_regressor_name
std::stack< std::tuple< std::string, reduction_setup_fn > >	reduction_stack
std::vector< std::string >	enabled_reductions
std::vector< std::unique_ptr< VW::io::writer > >	final_prediction_sink
std::unique_ptr< VW::io::writer >	raw_prediction
void(*	print )(VW::io::writer *, float, float, v_array< char >)
void(*	print_by_ref )(VW::io::writer *, float, float, const v_array< char > &)
void(*	print_text )(VW::io::writer *, std::string, v_array< char >)
void(*	print_text_by_ref )(VW::io::writer *, const std::string &, const v_array< char > &)
std::unique_ptr< loss_function >	loss
char *	program_name
bool	stdin_off
bool	no_daemon = false
float	initial_t
float	eta
float	eta_decay_rate
time_t	init_time
std::string	final_regressor_name
parameters	weights
size_t	max_examples
bool	hash_inv
bool	print_invert
bool	progress_add
float	progress_arg
std::map< uint64_t, std::string >	index_name_map
label_type_t	label_type

Constructor & Destructor Documentation

vw::vw

(

)

vw::~vw

(

)

vw::vw ( const vw &  )

delete

vw::vw ( const vw &&  )

delete

Member Function Documentation

void vw::finish_example

(

example &

)

void vw::finish_example

(

multi_ex &

)

std::shared_ptr<rand_state> vw::get_random_state ( )

inline

void vw::learn

(

example &

)

void vw::learn

(

multi_ex &

)

size_t vw::length ( )

inline

vw& vw::operator= ( const vw &  )

delete

vw& vw::operator= ( const vw &&  )

delete

void vw::predict

(

example &

)

void vw::predict

(

multi_ex &

)

Member Data Documentation

bool vw::active

bool vw::add_constant

std::array<uint64_t, NUM_NAMESPACES> vw::affix_features

AllReduce* vw::all_reduce

AllReduceType vw::all_reduce_type

bool vw::audit

bool vw::bfgs

bool vw::chain_hash_json = false

size_t vw::check_holdout_every_n_passes

VW::LEARNER::base_learner* vw::cost_sensitive

uint64_t vw::current_pass

bool vw::daemon

std::string vw::data_filename

bool vw::default_bits

void(* vw::delete_prediction) (void *)

std::vector<std::string> vw::dictionary_path

bool vw::do_reset_source

bool vw::early_terminate

std::vector<std::string> vw::enabled_reductions

float vw::eta

float vw::eta_decay_rate

parser* vw::example_parser

std::string vw::feature_mask

std::vector<std::unique_ptr<VW::io::writer> > vw::final_prediction_sink

std::string vw::final_regressor_name

bool vw::hash_inv

uint32_t vw::hash_seed

bool vw::hessian_on

uint32_t vw::holdout_after

uint32_t vw::holdout_period

bool vw::holdout_set_off

std::string vw::id

std::array<bool, NUM_NAMESPACES> vw::ignore

std::array<bool, NUM_NAMESPACES> vw::ignore_linear

bool vw::ignore_some

bool vw::ignore_some_linear

std::map<uint64_t, std::string> vw::index_name_map

time_t vw::init_time

float vw::initial_constant

std::vector<std::string> vw::initial_regressors

float vw::initial_t

float vw::initial_weight

std::vector<std::vector<namespace_index> > vw::interactions

std::string vw::inv_hash_regressor_name

bool vw::invariant_updates

VW::LEARNER::base_learner* vw::l

float vw::l1_lambda

float vw::l2_lambda

label_type_t vw::label_type

uint32_t vw::lda

std::array<uint32_t, NUM_NAMESPACES> vw::limit

std::vector<std::string> vw::limit_strings

std::vector<dictionary_info> vw::loaded_dictionaries

vw_logger vw::logger

std::unique_ptr<loss_function> vw::loss

size_t vw::max_examples

VW::version_struct vw::model_file_ver

std::array<std::vector<std::shared_ptr<feature_dict> >, NUM_NAMESPACES> vw::namespace_dictionaries {}

bool vw::no_bias

bool vw::no_daemon = false

bool vw::nonormalize

bool vw::normal_weights

size_t vw::normalized_idx

double vw::normalized_sum_norm_x

uint32_t vw::num_bits

size_t vw::num_children

size_t vw::numpasses

VW::config::options_i* vw::options

uint64_t vw::parse_mask

std::thread vw::parse_thread

size_t vw::pass_length

size_t vw::passes_complete

std::string vw::per_feature_regularizer_input

std::string vw::per_feature_regularizer_output

std::string vw::per_feature_regularizer_text

bool vw::permutations

float vw::power_t

bool vw::preserve_performance_counters

void(* vw::print) (VW::io::writer *, float, float, v_array< char >)

void(* vw::print_by_ref) (VW::io::writer *, float, float, const v_array< char > &)

bool vw::print_invert

void(* vw::print_text) (VW::io::writer *, std::string, v_array< char >)

void(* vw::print_text_by_ref) (VW::io::writer *, const std::string &, const v_array< char > &)

char* vw::program_name

bool vw::progress_add

float vw::progress_arg

bool vw::random_positive_weights

uint64_t vw::random_seed

bool vw::random_weights

std::unique_ptr<VW::io::writer> vw::raw_prediction

std::array<unsigned char, NUM_NAMESPACES> vw::redefine

bool vw::redefine_some

std::stack<std::tuple<std::string, reduction_setup_fn> > vw::reduction_stack

int vw::reg_mode

bool vw::save_per_pass

bool vw::save_resume

VW::LEARNER::single_learner* vw::scorer

shared_data* vw::sd

void* vw::searchstr

void(* vw::set_minmax) (shared_data *sd, float label)

bool vw::should_delete_options = false

std::unique_ptr<VW::kskip_ngram_transformer> vw::skip_gram_transformer

std::array<bool, NUM_NAMESPACES> vw::spelling_features

bool vw::stdin_off

std::unique_ptr<VW::io::writer> vw::stdout_adapter

std::string vw::text_regressor_name

bool vw::tnormal_weights

vw_ostream vw::trace_message

bool vw::training

bool vw::vw_is_main = false

parameters vw::weights

uint32_t vw::wpp

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The documentation for this struct was generated from the following file:

• /__w/vowpal_wabbit/vowpal_wabbit/vowpalwabbit/global_data.h