Source code for optuna.trial._frozen

import datetime
import warnings

from optuna import distributions
from optuna import logging
from optuna.trial._state import TrialState
from optuna import type_checking

if type_checking.TYPE_CHECKING:
    from typing import Any  # NOQA
    from typing import Dict  # NOQA
    from typing import Optional  # NOQA
    from typing import Sequence  # NOQA
    from typing import Union  # NOQA

    from optuna.distributions import BaseDistribution  # NOQA
    from optuna.distributions import CategoricalChoiceType  # NOQA
    from optuna.study import Study  # NOQA

    FloatingPointDistributionType = Union[
        distributions.UniformDistribution, distributions.LogUniformDistribution
    ]

_logger = logging.get_logger(__name__)


[docs]class FrozenTrial(object): """Status and results of a :class:`~optuna.trial.Trial`. Attributes: number: Unique and consecutive number of :class:`~optuna.trial.Trial` for each :class:`~optuna.study.Study`. Note that this field uses zero-based numbering. state: :class:`TrialState` of the :class:`~optuna.trial.Trial`. value: Objective value of the :class:`~optuna.trial.Trial`. datetime_start: Datetime where the :class:`~optuna.trial.Trial` started. datetime_complete: Datetime where the :class:`~optuna.trial.Trial` finished. params: Dictionary that contains suggested parameters. user_attrs: Dictionary that contains the attributes of the :class:`~optuna.trial.Trial` set with :func:`optuna.trial.Trial.set_user_attr`. intermediate_values: Intermediate objective values set with :func:`optuna.trial.Trial.report`. """ def __init__( self, number, # type: int state, # type: TrialState value, # type: Optional[float] datetime_start, # type: Optional[datetime.datetime] datetime_complete, # type: Optional[datetime.datetime] params, # type: Dict[str, Any] distributions, # type: Dict[str, BaseDistribution] user_attrs, # type: Dict[str, Any] system_attrs, # type: Dict[str, Any] intermediate_values, # type: Dict[int, float] trial_id, # type: int ): # type: (...) -> None self.number = number self.state = state self.value = value self.datetime_start = datetime_start self.datetime_complete = datetime_complete self.params = params self.user_attrs = user_attrs self.system_attrs = system_attrs self.intermediate_values = intermediate_values self._distributions = distributions self._trial_id = trial_id # Ordered list of fields required for `__repr__`, `__hash__` and dataframe creation. # TODO(hvy): Remove this list in Python 3.6 as the order of `self.__dict__` is preserved. _ordered_fields = [ "number", "value", "datetime_start", "datetime_complete", "params", "_distributions", "user_attrs", "system_attrs", "intermediate_values", "_trial_id", "state", ] def __eq__(self, other): # type: (Any) -> bool if not isinstance(other, FrozenTrial): return NotImplemented return other.__dict__ == self.__dict__ def __lt__(self, other): # type: (Any) -> bool if not isinstance(other, FrozenTrial): return NotImplemented return self.number < other.number def __le__(self, other): # type: (Any) -> bool if not isinstance(other, FrozenTrial): return NotImplemented return self.number <= other.number def __hash__(self): # type: () -> int return hash(tuple(getattr(self, field) for field in self._ordered_fields)) def __repr__(self): # type: () -> str return "{cls}({kwargs})".format( cls=self.__class__.__name__, kwargs=", ".join( "{field}={value}".format( field=field if not field.startswith("_") else field[1:], value=repr(getattr(self, field)), ) for field in self._ordered_fields ), ) def _validate(self): # type: () -> None if self.datetime_start is None: raise ValueError("`datetime_start` is supposed to be set.") if self.state.is_finished(): if self.datetime_complete is None: raise ValueError("`datetime_complete` is supposed to be set for a finished trial.") else: if self.datetime_complete is not None: raise ValueError( "`datetime_complete` is supposed to be None for an unfinished trial." ) if self.state == TrialState.COMPLETE and self.value is None: raise ValueError("`value` is supposed to be set for a complete trial.") if set(self.params.keys()) != set(self.distributions.keys()): raise ValueError( "Inconsistent parameters {} and distributions {}.".format( set(self.params.keys()), set(self.distributions.keys()) ) ) for param_name, param_value in self.params.items(): distribution = self.distributions[param_name] param_value_in_internal_repr = distribution.to_internal_repr(param_value) if not distribution._contains(param_value_in_internal_repr): raise ValueError( "The value {} of parameter '{}' isn't contained in the distribution " "{}.".format(param_value, param_name, distribution) ) @property def distributions(self): # type: () -> Dict[str, BaseDistribution] """Dictionary that contains the distributions of :attr:`params`.""" return self._distributions @distributions.setter def distributions(self, value): # type: (Dict[str, BaseDistribution]) -> None self._distributions = value @property def trial_id(self): # type: () -> int """Return the trial ID. .. deprecated:: 0.19.0 The direct use of this attribute is deprecated and it is recommended that you use :attr:`~optuna.trial.FrozenTrial.number` instead. Returns: The trial ID. """ warnings.warn( "The use of `FrozenTrial.trial_id` is deprecated. " "Please use `FrozenTrial.number` instead.", DeprecationWarning, ) _logger.warning( "The use of `FrozenTrial.trial_id` is deprecated. " "Please use `FrozenTrial.number` instead." ) return self._trial_id @property def last_step(self): # type: () -> Optional[int] if len(self.intermediate_values) == 0: return None else: return max(self.intermediate_values.keys()) @property def duration(self): # type: () -> Optional[datetime.timedelta] """Return the elapsed time taken to complete the trial. Returns: The duration. """ if self.datetime_start and self.datetime_complete: return self.datetime_complete - self.datetime_start else: return None