class_docstr: Adapter for to :class:`~optuna.multi_objective.samplers.BaseMultiObjectiveSampler`.
  
  This class implements the :class:`~optuna.samplers.BaseSampler` interface.
  When a method is invoked, the handling will be delegated to the given
  :class:`~optuna.multi_objective.samplers.BaseMultiObjectiveSampler` instance.
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code: def sample_independent(
      self,
      study: Study,
      trial: FrozenTrial,
      param_name: str,
      param_distribution: BaseDistribution,
  ) -> Any:
      mo_study = multi_objective.study.MultiObjectiveStudy(study)
      mo_trial = multi_objective.trial.FrozenMultiObjectiveTrial(
          mo_study.n_objectives, trial
      )
      return self._mo_sampler.sample_independent(
          mo_study, mo_trial, param_name, param_distribution
      )
  
file_path: optuna/optuna/multi_objective/samplers/_adapter.py
imports: from typing import Any
  from typing import Dict
  from optuna import multi_objective
  from optuna.distributions import BaseDistribution
  from optuna.samplers import BaseSampler
  from optuna.study import Study
  from optuna.trial import FrozenTrial
label_desc: Use image node_id 4 for calling the _MultiObjectiveSamplerAdapter obj's underlying member method code with example usage: obj.sample_independent(study, trial, param_name, param_distribution) and returns: self