class_docstr: Status and results of a :class:`~optuna.trial.Trial`.
  
  An object of this class has the same methods as :class:`~optuna.trial.Trial`, but is not
  associated with, nor has any references to a :class:`~optuna.study.Study`.
  
  It is therefore not possible to make persistent changes to a storage from this object by
  itself, for instance by using :func:`~optuna.trial.FrozenTrial.set_user_attr`.
  
  It will suggest the parameter values stored in :attr:`params` and will not sample values from
  any distributions.
  
  It can be passed to objective functions (see :func:`~optuna.study.Study.optimize`) and is
  useful for deploying optimization results.
  
  Example:
  
      Re-evaluate an objective function with parameter values optimized study.
  
      .. testcode::
  
          import optuna
  
  
          def objective(trial):
              x = trial.suggest_float("x", -1, 1)
              return x**2
  
  
          study = optuna.create_study()
          study.optimize(objective, n_trials=3)
  
          assert objective(study.best_trial) == study.best_value
  
  .. note::
      Instances are mutable, despite the name.
      For instance, :func:`~optuna.trial.FrozenTrial.set_user_attr` will update user attributes
      of objects in-place.
  
  
      Example:
  
          Overwritten attributes.
  
          .. testcode::
  
              import copy
              import datetime
  
              import optuna
  
  
              def objective(trial):
                  x = trial.suggest_float("x", -1, 1)
  
                  # this user attribute always differs
                  trial.set_user_attr("evaluation time", datetime.datetime.now())
  
                  return x**2
  
  
              study = optuna.create_study()
              study.optimize(objective, n_trials=3)
  
              best_trial = study.best_trial
              best_trial_copy = copy.deepcopy(best_trial)
  
              # re-evaluate
              objective(best_trial)
  
              # the user attribute is overwritten by re-evaluation
              assert best_trial.user_attrs != best_trial_copy.user_attrs
  
  .. note::
      Please refer to :class:`~optuna.trial.Trial` for details of methods and properties.
  
  
  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`.
          ``value`` and ``values`` must not be specified at the same time.
      values:
          Sequence of objective values of the :class:`~optuna.trial.Trial`.
          The length is greater than 1 if the problem is multi-objective optimization.
          ``value`` and ``values`` must not be specified at the same time.
      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.
      distributions:
          Dictionary that contains the distributions of :attr:`params`.
      user_attrs:
          Dictionary that contains the attributes of the :class:`~optuna.trial.Trial` set with
          :func:`optuna.trial.Trial.set_user_attr`.
      system_attrs:
          Dictionary that contains the attributes of the :class:`~optuna.trial.Trial` set with
          :func:`optuna.trial.Trial.set_system_attr`.
      intermediate_values:
          Intermediate objective values set with :func:`optuna.trial.Trial.report`.
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code: def system_attrs(self) -> Dict[str, Any]:
      return self._system_attrs
  
imports: import datetime
  from typing import Any
  from typing import cast
  from typing import Dict
  from typing import List
  from typing import Mapping
  from typing import Optional
  from typing import overload
  from typing import Sequence
  import warnings
  from optuna import distributions
  from optuna import logging
  from optuna._convert_positional_args import convert_positional_args
  from optuna._deprecated import deprecated_func
  from optuna._typing import JSONSerializable
  from optuna.distributions import _convert_old_distribution_to_new_distribution
  from optuna.distributions import BaseDistribution
  from optuna.distributions import CategoricalChoiceType
  from optuna.distributions import CategoricalDistribution
  from optuna.distributions import FloatDistribution
  from optuna.distributions import IntDistribution
  from optuna.trial._base import _SUGGEST_INT_POSITIONAL_ARGS
  from optuna.trial._base import BaseTrial
  from optuna.trial._state import TrialState
label_desc: Use image node_id 39 for calling the FrozenTrial obj's underlying member method code with example usage: obj.system_attrs() and returns: self