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()