parameters Class Reference

#include <array_parameters.h>

Public Member Functions
weight &	operator[] (size_t i)
uint32_t	stride_shift ()
uint32_t	stride ()
uint64_t	mask ()
uint64_t	seeded ()
void	shallow_copy (const parameters &input)
void	set_zero (size_t offset)
void	share (size_t length)
void	stride_shift (uint32_t stride_shift)
weight &	strided_index (size_t index)
bool	not_null ()

Public Attributes
bool	adaptive
bool	normalized
bool	sparse
dense_parameters	dense_weights
sparse_parameters	sparse_weights

Detailed Description

Definition at line 226 of file array_parameters.h.

Member Function Documentation

mask()

uint64_t parameters::mask ( )

inline

Definition at line 260 of file array_parameters.h.

References dense_parameters::mask(), and sparse_parameters::mask().

Referenced by Search::add_new_feature(), recall_tree_ns::add_node_id_feature(), GD::audit_feature(), audit_regressor_feature(), copy_example_to_adf(), flatten_example(), VW::get_features(), Search::search::get_mask(), learn_batch(), learn_with_metrics(), MARGINAL::make_marginal(), mf_print_offset_features(), multiply(), predict_or_learn(), MWT::predict_or_learn(), GraphTask::setup(), MARGINAL::update_marginal(), MWT::value_policy(), wid_mask(), and wid_mask_un_shifted().

  {
    if (sparse)
      return sparse_weights.mask();
    else
      return dense_weights.mask();
  }

not_null()

bool parameters::not_null ( )

inline

Definition at line 319 of file array_parameters.h.

References dense_parameters::not_null(), and sparse_parameters::not_null().

Referenced by flatten_example().

  {
    if (sparse)
      return sparse_weights.not_null();
    else
      return dense_weights.not_null();
  }

operator[]()

weight& parameters::operator[] ( size_t  i )

inline

Definition at line 236 of file array_parameters.h.

  {
    if (sparse)
      return sparse_weights[i];
    else
      return dense_weights[i];
  }

seeded()

uint64_t parameters::seeded ( )

inline

Definition at line 268 of file array_parameters.h.

References dense_parameters::seeded(), and sparse_parameters::seeded().

Referenced by VW::finish().

  {
    if (sparse)
      return sparse_weights.seeded();
    else
      return dense_weights.seeded();
  }

set_zero()

void parameters::set_zero ( size_t  offset )

inline

Definition at line 284 of file array_parameters.h.

References dense_parameters::set_zero(), and sparse_parameters::set_zero().

Referenced by parse_mask_regressor_args(), zero_derivative(), zero_preconditioner(), and zero_state().

  {
    if (sparse)
      sparse_weights.set_zero(offset);
    else
      dense_weights.set_zero(offset);
  }

shallow_copy()

void parameters::shallow_copy ( const parameters &  input )

inline

Definition at line 276 of file array_parameters.h.

References dense_weights, dense_parameters::shallow_copy(), sparse_parameters::shallow_copy(), and sparse_weights.

Referenced by VW::seed_vw_model().

  {
    if (sparse)
      sparse_weights.shallow_copy(input.sparse_weights);
    else
      dense_weights.shallow_copy(input.dense_weights);
  }

share()

void parameters::share ( size_t  length )

inline

Definition at line 293 of file array_parameters.h.

References dense_parameters::share(), and sparse_parameters::share().

Referenced by enable_sources().

  {
    if (sparse)
      sparse_weights.share(length);
    else
      dense_weights.share(length);
  }

stride()

uint32_t parameters::stride ( )

inline

Definition at line 252 of file array_parameters.h.

References dense_parameters::stride(), and sparse_parameters::stride().

Referenced by bfgs_setup(), VW::get_stride(), learn_batch(), OjaNewton_setup(), and save_load().

  {
    if (sparse)
      return sparse_weights.stride();
    else
      return dense_weights.stride();
  }

stride_shift() [1/2]

uint32_t parameters::stride_shift ( )

inline

Definition at line 244 of file array_parameters.h.

References dense_parameters::stride_shift(), and sparse_parameters::stride_shift().

Referenced by accumulate_weighted_avg(), Search::add_example_conditioning(), Search::add_neighbor_features(), Search::add_new_feature(), recall_tree_ns::add_node_id_feature(), ezexample::addf(), GD::audit_feature(), audit_regressor_feature(), audit_regressor_lda(), autolink_setup(), bfgs_setup(), CCB::ccb_explore_adf_setup(), copy_example_to_adf(), VW::export_example(), DepParserTask::extract_features(), finish_setup(), flatten_example(), ftrl_setup(), gd_mf_setup(), VW::get_features(), Search::search::get_stride_shift(), VW::get_weight(), init_global(), lda_setup(), learn_with_metrics(), OjaNewton_setup(), parse_sources(), predict_or_learn(), MWT::predict_or_learn(), GD::print_lda_features(), print_setup(), MARGINAL::save_load(), save_load(), memory_tree_ns::save_load_memory_tree(), VW::set_weight(), GraphTask::setup(), VW::setup_example(), stride_shift(), stride_un_shift(), svrg_setup(), un_ft_offset(), and MWT::value_policy().

  {
    if (sparse)
      return sparse_weights.stride_shift();
    else
      return dense_weights.stride_shift();
  }

stride_shift() [2/2]

void parameters::stride_shift ( uint32_t  stride_shift )

inline

Definition at line 303 of file array_parameters.h.

References dense_parameters::stride_shift(), and sparse_parameters::stride_shift().

  {
    if (sparse)
      sparse_weights.stride_shift(stride_shift);
    else
      dense_weights.stride_shift(stride_shift);
  }

strided_index()

weight& parameters::strided_index ( size_t  index )

inline

Definition at line 311 of file array_parameters.h.

References dense_parameters::strided_index(), and sparse_parameters::strided_index().

Referenced by OjaNewton::check(), OjaNewton::initialize_Z(), and save_load().

  {
    if (sparse)
      return sparse_weights.strided_index(index);
    else
      return dense_weights.strided_index(index);
  }

Member Data Documentation

adaptive

bool parameters::adaptive

Definition at line 229 of file array_parameters.h.

Referenced by accumulate_weighted_avg(), GD::audit_feature(), GD::end_pass(), GD::save_load(), GD::save_load_online_state(), GD::set_learn(), and GD::setup().

dense_weights

dense_parameters parameters::dense_weights

Definition at line 233 of file array_parameters.h.

Referenced by accumulate(), accumulate_avg(), accumulate_weighted_avg(), add_regularization(), bfgs_iter_middle(), bfgs_iter_start(), compute_coherence_metrics(), derivative_in_direction(), direction_magnitude(), end_examples(), finalize_preconditioner(), GD::foreach_feature(), INTERACTIONS::generate_interactions(), get_top_weights(), init_driver(), initialize_regressor(), GD::inline_predict(), mf_predict(), mf_train(), multipredict(), GD::multipredict(), preconditioner_to_regularizer(), regularizer_direction_magnitude(), regularizer_to_weight(), sanity_check_state(), save_load(), GD::save_load(), GD::save_load_online_state(), GD::save_load_regressor(), shallow_copy(), GD::sync_weights(), update_weight(), and wolfe_eval().

normalized

bool parameters::normalized

Definition at line 230 of file array_parameters.h.

Referenced by GD::save_load_online_state(), GD::set_learn(), and GD::setup().

sparse

bool parameters::sparse

Definition at line 232 of file array_parameters.h.

Referenced by accumulate(), accumulate_avg(), accumulate_weighted_avg(), add_regularization(), audit_regressor(), bfgs_iter_middle(), bfgs_iter_start(), compute_coherence_metrics(), derivative_in_direction(), direction_magnitude(), end_examples(), finalize_preconditioner(), GD::foreach_feature(), INTERACTIONS::generate_interactions(), get_top_weights(), init_driver(), initialize_regressor(), GD::inline_predict(), mf_predict(), mf_train(), multipredict(), GD::multipredict(), parse_args(), preconditioner_to_regularizer(), regularizer_direction_magnitude(), regularizer_to_weight(), sanity_check_state(), save_load(), GD::save_load(), GD::save_load_online_state(), GD::save_load_regressor(), GD::sync_weights(), update_weight(), and wolfe_eval().

sparse_weights

sparse_parameters parameters::sparse_weights

Definition at line 234 of file array_parameters.h.

Referenced by accumulate(), accumulate_avg(), accumulate_weighted_avg(), add_regularization(), audit_regressor(), bfgs_iter_middle(), bfgs_iter_start(), compute_coherence_metrics(), derivative_in_direction(), direction_magnitude(), end_examples(), finalize_preconditioner(), GD::foreach_feature(), INTERACTIONS::generate_interactions(), get_top_weights(), init_driver(), initialize_regressor(), GD::inline_predict(), mf_predict(), mf_train(), multipredict(), GD::multipredict(), preconditioner_to_regularizer(), regularizer_direction_magnitude(), regularizer_to_weight(), sanity_check_state(), save_load(), GD::save_load(), GD::save_load_online_state(), GD::save_load_regressor(), shallow_copy(), GD::sync_weights(), update_weight(), and wolfe_eval().

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

• /mnt/c/w/linux/vowpal_wabbit/vowpalwabbit/array_parameters.h