internal Namespace Reference

Classes
struct	print_status
class	refinement_schedule
class	task_group
class	basic_exon_iterator
class	normalised_row_view
struct	dataset_example_impl
struct	dataset_example_impl< D, true >
struct	dataset_example_impl< D, false >
struct	has_regression_predictor
class	reg_oracle_storage
class	reg_oracle_storage< gp::individual, true >
class	reg_oracle_storage< gp::individual, false >
class	reg_oracle_storage< T, S >

Typedefs
template<class D>
using	dataset_example_t = typename dataset_example_impl<D>::type

Enumerations
enum class	phase { evolution , refinement }

Functions
void	merge_ct (auto &destination, const auto &source)
std::size_t	div_ceil (std::size_t x, std::size_t y)
template<Evaluator E>
std::size_t	set_evaluator_parallelism (std::size_t allocated, std::size_t min_samples_per_eval_thread, E &eva)
constexpr std::size_t	normalised_column_count (std::size_t raw_count, std::optional< std::size_t > output_index) noexcept
constexpr std::optional< std::size_t >	raw_column_index (std::size_t idx, std::optional< std::size_t > output_index) noexcept
value_t	lexical_cast (value_t v, domain_t d)
template<class T>
void	inplace_trim (T &v)
template<class P>
std::unique_ptr< basic_oracle >	make_basic_oracle (P &&p)
template<LayeredPopulation P>
std::size_t	random_layer_index (const P &p)

Variables
template<class F, class P>
constexpr bool	has_regression_predictor_v
	Convenience variable template for has_regression_predictor.

Detailed Description

The contents of this namespace isn't intended for general consumption: it contains implementation details, not the interface. It's recommended giving details their own file and tucking it away in a detail folder.

Function Documentation

div_ceil()

std::size_t internal::div_ceil ( std::size_t x, std::size_t y )

inlinenodiscard

Fast ceiling integer division.

Parameters

[in]	x	dividend
[in]	y	divisor

Returns

ceiling of the quotient

set_evaluator_parallelism()

template<Evaluator E>

std::size_t internal::set_evaluator_parallelism ( std::size_t allocated, std::size_t min_samples_per_eval_thread, E & eva )

nodiscard

Configures parallel dataset evaluation for an evaluator.

Parameters

[in]	allocated	number of concurrent worker tasks
[in]	min_samples_per_eval_thread	minimum number of samples per thread
[in,out]	eva	evaluator instance to configure

Returns

number of helper threads assigned, or 0 if unsupported or disabled

Distributes surplus hardware thread capacity among the allocated tasks and forwards the configuration to the evaluator if supported.

Variable Documentation

has_regression_predictor_v

template<class F, class P>

bool internal::has_regression_predictor_v

inlineconstexpr

Initial value:

=
  has_regression_predictor<F, P>::value

Convenience variable template for has_regression_predictor.