class_docstr: Base class for multi-objective samplers.
  
  The abstract methods of this class are the same as ones defined by
  :class:`~optuna.samplers.BaseSampler` except for taking
  multi-objective versions of study and trial instances as the arguments.
docstr: Sample a parameter for a given distribution.
  
  This method is called only for the parameters not contained in the search space returned
  by :func:`~optuna.multi_objective.samplers.MultiObjectiveBaseSampler.sample_relative`
  method. This method is suitable for sampling algorithms that do not use the relationship
  between parameters such as random sampling.
  
  Args:
      study:
          Target study object.
      trial:
          Target trial object.
      param_name:
          Name of the sampled parameter.
      param_distribution:
          Distribution object that specifies a prior and/or scale of the sampling algorithm.
  
  Returns:
      A parameter value.
code: def sample_independent(
      self,
      study: "multi_objective.study.MultiObjectiveStudy",
      trial: "multi_objective.trial.FrozenMultiObjectiveTrial",
      param_name: str,
      param_distribution: BaseDistribution,
  ) -> Any:
      """Sample a parameter for a given distribution.
  
      This method is called only for the parameters not contained in the search space returned
      by :func:`~optuna.multi_objective.samplers.MultiObjectiveBaseSampler.sample_relative`
      method. This method is suitable for sampling algorithms that do not use the relationship
      between parameters such as random sampling.
  
      Args:
          study:
              Target study object.
          trial:
              Target trial object.
          param_name:
              Name of the sampled parameter.
          param_distribution:
              Distribution object that specifies a prior and/or scale of the sampling algorithm.
  
      Returns:
          A parameter value.
  
      """
  
      raise NotImplementedError
  
file_path: optuna/optuna/multi_objective/samplers/_base.py
imports: import abc
  from typing import Any
  from typing import Dict
  from optuna import multi_objective
  from optuna._deprecated import deprecated_class
  from optuna.distributions import BaseDistribution
label_desc: Use image node_id 3 for calling the BaseMultiObjectiveSampler obj's underlying member method code with example usage: obj.sample_independent(study, trial, param_name, param_distribution) without return types