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This commit is contained in:
Vitor Santos Costa
@@ -204,6 +204,8 @@
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%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%% @file problog/flags
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:-module(flags, [problog_define_flag/4,
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problog_define_flag/5,
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problog_define_flag/6,
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@@ -218,6 +220,314 @@
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:- use_module(logger).
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:- use_module(library(system), [file_exists/1, delete_file/1]).
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/** @defgroup ProbLogMiscellaneous ProbLog Miscellaneous Predicates
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@ingroup problog
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@{
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Both the learning and the inference module have various parameters, or flags, that can be adjusted by the user.
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The following predicates are defined by ProbLog to access and set these flags.
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*/
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/**
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* @pred problog_flags
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*
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This predicate lists all the flags name, value, domain and description.
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*/
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/** @pred problog_flag(+Name, -Value)
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This predicate gives the value of the flag with the specified name. The supported flags are:
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+ use_db_trie
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Flag telling whether to use the builtin trie to trie transformation.
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The possible values for this flag are true or false.
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+ db_trie_opt_lvl
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Sets the optimization level for the trie to trie transformation
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The possible values for this flag are any integer
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+ compare_opt_lvl
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Flag telling whether to use comparison mode for the optimization level.
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The possible values for this flag are true or false.
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+ db_min_prefix
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Sets the minimum size of the prefix for dbtrie to optimize.
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The possible values for this flag are any integer
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+ use_naive_trie
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Flag telling whether to use the naive algorithm to generate bdd scripts.
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The possible values for this flag are true or false.
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+ use_old_trie
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Flag telling whether to use the old not nested trie to trie transformation.
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The possible values for this flag are true or false.
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+ use_dec_trie
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Flag telling whether to use the decomposition method.
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The possible values for this flag are true or false.
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+ subset_check
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Flag telling whether to perform subset check in nested tries.
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The possible values for this flag are true or false.
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+ deref_terms
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Flag telling whether to dereference BDD terms after their last use.
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The possible values for this flag are true or false.
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+ trie_preprocess
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Flag telling whether to perform a preprocess step to nested tries.
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The possible values for this flag are true or false.
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+ refine_anclst
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Flag telling whether to refine the ancestor list with their children.
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The possible values for this flag are true or false.
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+ anclst_represent
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Flag that sets the representation of the ancestor list.
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The possible values for this flag are list or integer
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+ max_depth
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Sets the maximum proof depth.
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The possible values for this flag are any integer.
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+ retain_tables
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Flag telling whether to retain tables after the query.
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The possible values for this flag are true or false.
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+ mc_batchsize
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Flag related to Monte Carlo Sampling that sets the number of samples before update.
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The possible values for this flag are any integer greater than zero.
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+ min_mc_samples
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Flag related to Monte Carlo Sampling that sets the minimum number of samples before convergence. The possible values for this flag are any integer greater than or equal to zero.
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+ max_mc_samples
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Flag related to Monte Carlo Sampling that sets the maximum number of samples waiting to converge.
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The possible values for this flag are any integer greater than or equal to zero.
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+ randomizer
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Flag related to Monte Carlo Sampling telling whether the random numbers are repeatable or not.
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The possible values for this flag are repeatable or nonrepeatable.
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+ search_method
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Flag related to DNF Monte Carlo Sampling that sets the search method for picking the proof.
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The possible values for this flag are linear or binary.
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+ represent_world
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Flag related to Monte Carlo Sampling that sets the structure that represents sampled world.
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The possible values for this flag are list, record, array or hash_table
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+ first_threshold
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Flag related to inference that sets the starting threshold of iterative deepening.
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The possible values for this flag are a number in the interval (0,1).
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+ last_threshold
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Flag related to inference that sets the stopping threshold of iterative deepening.
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The possible values for this flag are a number in the interval (0,1).
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+ id_stepsize
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Flag related to inference that sets the threshold shrinking factor of iterative deepening.
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The possible values for this flag are a number in the interval [0,1].
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+ prunecheck
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Flag related to inference telling whether to stop derivations including all facts of known proofs.
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The possible values for this flag are on or off.
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+ maxsteps
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Flag related to inference that sets the max. number of prob. steps per derivation.
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The possible values for this flag are any integer greater than zero.
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+ mc_logfile
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Flag related to MCMC that sets the logfile for montecarlo.
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The possible values for this flag are any valid filename.
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+ bdd_time
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Flag related to BDD that sets the BDD computation timeout in seconds.
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The possible values for this flag are any integer greater than zero.
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+ bdd_par_file
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Flag related to BDD that sets the file for BDD variable parameters.
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The possible values for this flag are any valid filename.
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+ bdd_result
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Flag related to BDD that sets the file to store result calculated from BDD.
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The possible values for this flag are any valid filename.
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+ bdd_file
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Flag related to BDD that sets the file for the BDD script.
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The possible values for this flag are any valid filename.
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+ save_bdd
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Flag related to BDD telling whether to save BDD files for (last) lower bound.
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The possible values for this flag are true or false.
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+ dynamic_reorder
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Flag related to BDD telling whether to use dynamic re-ordering for BDD.
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The possible values for this flag are true or false.
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+ bdd_static_order
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Flag related to BDD telling whether to use static order.
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The possible values for this flag are true or false.
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+ static_order_file
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Flag related to BDD that sets the file for BDD static order.
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The possible values for this flag are any valid filename.
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+ verbose
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Flag telling whether to output intermediate information.
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The possible values for this flag are true or false.
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+ show_proofs
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Flag telling whether to output proofs.
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The possible values for this flag are true or false.
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+ triedump
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Flag telling whether to generate the file: trie_file containing the trie structure.
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The possible values for this flag are true or false.
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+ dir
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Flag telling the location of the output files directory.
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The possible values for this flag are any valid directory name.
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*/
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/** @pred set_problog_flag(+Name, +Value)
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the predicate sets the value of the given flag. The supported flags are the ones listed in above
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*/
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/** @pred learning_flags
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the predicate sets the value of the given flag. The supported flags are the ones listed in above
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*/
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/** @pred learning_flag(+Name, -Value)
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This predicate gives the value of the learning flag with the specified name. The supported flags are:
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+ output_directory
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Flag setting the directory where to store results.
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The possible values for this flag are any valid path name.
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+ query_directory
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Flag setting the directory where to store BDD files.
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The possible values for this flag are any valid path name.
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+ verbosity_level
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Flag telling how much output shall be given.
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The possible values for this flag are an integer between 0 and 5 (0=nothing, 5=all).
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+ reuse_initialized_bdds
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Flag telling whether to reuse BDDs from previous runs.
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The possible values for this flag are true or false.
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+ rebuild_bdds
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Flag telling whether to rebuild BDDs every nth iteration.
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The possible values for this flag are any integer greater or equal to zero (0=never).
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+ check_duplicate_bdds
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Flag telling whether to store intermediate results in hash table.
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The possible values for this flag are true or false.
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+ init_method
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Flag setting the ProbLog predicate to search proofs.
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The possible values for this flag are of the form: (+Query,-P,+BDDFile,+ProbFile,+Call). For example: A,B,C,D,problog_kbest_save(A,100,B,E,C,D)
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+ probability_initializer
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Flag setting the ProbLog predicate to initialize probabilities.
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The possible values for this flag are of the form: (+FactID,-P,+Call). For example: A,B,random_probability(A,B)
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+ log_frequency
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Flag telling whether to log results every nth iteration.
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The possible values for this flag are any integer greater than zero.
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+ alpha
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Flag setting the weight of negative examples.
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The possible values for this flag are number or "auto" (auto=n_p/n_n).
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+ slope
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Flag setting the slope of the sigmoid function.
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The possible values for this flag are any real number greater than zero.
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+ learning_rate
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Flag setting the default Learning rate (if line_search=false)
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The possible values for this flag are any number greater than zero or "examples``
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+ line_search
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Flag telling whether to use line search to estimate the learning rate.
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The possible values for this flag are true or false.
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+ line_search_tau
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Flag setting the Tau value for line search.
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The possible values for this flag are a number in the interval (0,1).
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+ line_search_tolerance
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Flag setting the tolerance value for line search.
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The possible values for this flag are any number greater than zero.
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+ line_search_interval
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Flag setting the interval for line search.
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*/
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problog_define_flag(Flag, Type, Description, DefaultValue):-
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flag_define(Flag, Type, DefaultValue, Description).
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@@ -405,3 +715,5 @@ problog_flag_validate_interval( (V1,V2) ) :-
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V1<V2.
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*/
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%% @}
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