code: def _is_compatible_search_space(
      trans: _SearchSpaceTransform,
      search_space: Dict[str, BaseDistribution],
  ) -> bool:
      intersection_size = len(
          set(trans._search_space.keys()).intersection(
              search_space.keys()
          )
      )
      return (
          intersection_size
          == len(trans._search_space)
          == len(search_space)
      )
  
imports: from __future__ import annotations
  import copy
  import math
  import pickle
  from typing import Any
  from typing import Callable
  from typing import cast
  from typing import Dict
  from typing import List
  from typing import NamedTuple
  from typing import Optional
  from typing import Sequence
  from typing import Tuple
  from typing import TYPE_CHECKING
  from typing import Union
  import warnings
  import numpy
  import optuna
  from optuna import logging
  from optuna._imports import _LazyImport
  from optuna._transform import _SearchSpaceTransform
  from optuna.distributions import BaseDistribution
  from optuna.distributions import FloatDistribution
  from optuna.distributions import IntDistribution
  from optuna.exceptions import ExperimentalWarning
  from optuna.samplers import BaseSampler
  from optuna.samplers._lazy_random_state import LazyRandomState
  from optuna.search_space import IntersectionSearchSpace
  from optuna.study._study_direction import StudyDirection
  from optuna.trial import FrozenTrial
  from optuna.trial import TrialState
label_desc: Use image node_id 1 for calling a global function with example usage: _is_compatible_search_space(trans, search_space) and returns: unknown