code: def _is_contained(
      params: Dict[str, Any], search_space: Dict[str, BaseDistribution]
  ) -> bool:
      for param_name in params.keys():
          param, param_distribution = (
              params[param_name],
              search_space[param_name],
          )
  
          if not param_distribution._contains(
              param_distribution.to_internal_repr(param)
          ):
              return False
      return True
  
imports: from typing import Any
  from typing import Callable
  from typing import Dict
  from typing import List
  from typing import Optional
  from typing import Sequence
  import numpy
  from optuna._transform import _SearchSpaceTransform
  from optuna.distributions import BaseDistribution
  from optuna.distributions import FloatDistribution
  from optuna.distributions import IntDistribution
  from optuna.samplers.nsgaii._crossovers._base import BaseCrossover
  from optuna.study import Study
  from optuna.study import StudyDirection
  from optuna.trial import FrozenTrial
label_desc: Use image node_id 5 for calling a global function with example usage: _is_contained(params, search_space) and returns: True, False