optunahub.samplers.SimpleBaseSampler

class optunahub.samplers.SimpleBaseSampler(search_space: dict[str, BaseDistribution] | None = None, seed: int | None = None)

A simple base class to implement user-defined samplers.

__init__(search_space: dict[str, BaseDistribution] | None = None, seed: int | None = None) → None

Methods

__init__([search_space, seed])
after_trial(study, trial, state, values)	Trial post-processing.
before_trial(study, trial)	Trial pre-processing.
infer_relative_search_space(study, trial)	Infer the search space that will be used by relative sampling in the target trial.
reseed_rng()	Reseed sampler's random number generator.
sample_independent(study, trial, param_name, ...)	Sample a parameter for a given distribution.
sample_relative(study, trial, search_space)	Sample parameters in a given search space.