def __init__(
self,
independent_sampler: Optional[BaseSampler] = None,
warn_independent_sampling: bool = True,
skopt_kwargs: Optional[Dict[str, Any]] = None,
n_startup_trials: int = 1,
*,
consider_pruned_trials: bool = False,
) -> None:
_imports.check()
self._skopt_kwargs = skopt_kwargs or {}
if "dimensions" in self._skopt_kwargs:
del self._skopt_kwargs["dimensions"]
self._independent_sampler = independent_sampler or samplers.RandomSampler(
)
self._warn_independent_sampling = warn_independent_sampling
self._n_startup_trials = n_startup_trials
self._search_space = samplers.IntersectionSearchSpace()
self._consider_pruned_trials = consider_pruned_trials
if self._consider_pruned_trials:
warnings.warn(
"`consider_pruned_trials` option is an experimental feature."
" The interface can change in the future.",
ExperimentalWarning,
)
def __init__(
self,
independent_sampler=None,
warn_independent_sampling=True,
skopt_kwargs=None,
n_startup_trials=1,
):
# type: (Optional[BaseSampler], bool, Optional[Dict[str, Any]], int) -> None
_check_skopt_availability()
self._skopt_kwargs = skopt_kwargs or {}
if "dimensions" in self._skopt_kwargs:
del self._skopt_kwargs["dimensions"]
self._independent_sampler = independent_sampler or samplers.RandomSampler()
self._warn_independent_sampling = warn_independent_sampling
self._n_startup_trials = n_startup_trials
self._search_space = samplers.IntersectionSearchSpace()
def __init__(self,
independent_sampler: Optional[BaseSampler] = None,
warn_independent_sampling: bool = True,
skopt_kwargs: Optional[Dict[str, Any]] = None,
n_startup_trials: int = 1,
*,
consider_pruned_trials: bool = False) -> None:
_imports.check()
self._skopt_kwargs = skopt_kwargs or {}
if "dimensions" in self._skopt_kwargs:
del self._skopt_kwargs["dimensions"]
self._independent_sampler = independent_sampler or samplers.RandomSampler(
)
self._warn_independent_sampling = warn_independent_sampling
self._n_startup_trials = n_startup_trials
self._search_space = samplers.IntersectionSearchSpace()
self._consider_pruned_trials = consider_pruned_trials
if self._consider_pruned_trials:
self._raise_experimental_warning_for_consider_pruned_trials()