def __init__(
self,
space,
seed=None,
n_initial_points=20,
n_ei_candidates=24,
gamma=0.25,
equal_weight=False,
prior_weight=1.0,
full_weight_num=25,
max_retry=100,
parallel_strategy=None,
):
if n_initial_points < 2:
n_initial_points = 2
logger.warning(
"n_initial_points %s is not valid, set n_initial_points = 2",
str(n_initial_points),
)
if n_ei_candidates < 1:
n_ei_candidates = 1
logger.warning(
"n_ei_candidates %s is not valid, set n_ei_candidates = 1",
str(n_ei_candidates),
)
if parallel_strategy is None:
parallel_strategy = {
"of_type": "StatusBasedParallelStrategy",
"strategy_configs": {
"broken": {
"of_type": "MaxParallelStrategy",
},
},
}
self.strategy = strategy_factory.create(**parallel_strategy)
super(TPE, self).__init__(
space,
seed=seed,
n_initial_points=n_initial_points,
n_ei_candidates=n_ei_candidates,
gamma=gamma,
equal_weight=equal_weight,
prior_weight=prior_weight,
full_weight_num=full_weight_num,
max_retry=max_retry,
parallel_strategy=parallel_strategy,
)
def create_strategy(self, config=None, **kwargs):
"""Create the parallel strategy based on config.
Parameters
----------
config: dict, optional
The configuration for the parallel strategy. ``self.config`` will be used
if ``config`` is ``None``.
kwargs: dict
Values to override strategy configuration.
"""
config = copy.deepcopy(config or self.config)
config.update(kwargs)
return strategy_factory.create(**self.config)
def __init__(
self,
space,
seed=None,
min_points_in_model=None,
top_n_percent=15,
num_samples=64,
random_fraction=1 / 3,
bandwidth_factor=3,
min_bandwidth=1e-3,
parallel_strategy=None,
): # pylint: disable=too-many-arguments
if parallel_strategy is None:
parallel_strategy = {
"of_type": "StatusBasedParallelStrategy",
"strategy_configs": {
"broken": {
"of_type": "MaxParallelStrategy",
},
},
}
self.strategy = strategy_factory.create(**parallel_strategy)
super().__init__(
space,
seed=seed,
min_points_in_model=min_points_in_model,
top_n_percent=top_n_percent,
num_samples=num_samples,
random_fraction=random_fraction,
bandwidth_factor=bandwidth_factor,
min_bandwidth=min_bandwidth,
parallel_strategy=parallel_strategy,
)
self.trial_meta = {}
self.trial_results = {}
self.iteration = 0
self.iterations = []
fidelity_index = self.fidelity_index
if fidelity_index is None:
raise RuntimeError(SPACE_ERROR)
fidelity_dim = self.space[fidelity_index]
fidelity_dim: Fidelity = space[self.fidelity_index]
# NOTE: This isn't a Fidelity, it's a TransformedDimension<Fidelity>
from orion.core.worker.transformer import TransformedDimension
# NOTE: Currently bypassing (possibly more than one) `TransformedDimension` wrappers to get
# the 'low', 'high' and 'base' attributes.
while isinstance(fidelity_dim, TransformedDimension):
fidelity_dim = fidelity_dim.original_dimension
assert isinstance(fidelity_dim, Fidelity)
self.min_budget = fidelity_dim.low
self.max_budget = fidelity_dim.high
self.eta = fidelity_dim.base
self._setup()
def __init__(
self,
space: Space,
seed: int | Sequence[int] | None = None,
n_initial_points: int = 20,
n_ei_candidates: int = 24,
gamma: float = 0.25,
equal_weight: bool = False,
prior_weight: float = 1.0,
full_weight_num: int = 25,
max_retry: int = 100,
parallel_strategy: dict | None = None,
):
if n_initial_points < 2:
n_initial_points = 2
logger.warning(
"n_initial_points %s is not valid, set n_initial_points = 2",
str(n_initial_points),
)
if n_ei_candidates < 1:
n_ei_candidates = 1
logger.warning(
"n_ei_candidates %s is not valid, set n_ei_candidates = 1",
str(n_ei_candidates),
)
if parallel_strategy is None:
parallel_strategy = {
"of_type": "StatusBasedParallelStrategy",
"strategy_configs": {
"broken": {
"of_type": "MaxParallelStrategy",
},
},
}
self.strategy: ParallelStrategy = strategy_factory.create(**parallel_strategy)
super().__init__(
space,
seed=seed,
n_initial_points=n_initial_points,
n_ei_candidates=n_ei_candidates,
gamma=gamma,
equal_weight=equal_weight,
prior_weight=prior_weight,
full_weight_num=full_weight_num,
max_retry=max_retry,
parallel_strategy=parallel_strategy,
)
# TODO: Setting the attributes here so their types are registered. Need to get rid of
# overlap with super().__init__ somehow.
self.seed = seed
self.n_initial_points = n_initial_points
self.n_ei_candidates = n_ei_candidates
self.gamma = gamma
self.equal_weight = equal_weight
self.prior_weight = prior_weight
self.full_weight_num = full_weight_num
self.max_retry = max_retry
self.parallel_strategy = parallel_strategy
self._verify_space()