code: def get_preprocessor(
      space: gym.Space, include_multi_binary=False
  ) -> type:
      """Returns an appropriate preprocessor class for the given space."""
  
      _legacy_patch_shapes(space)
      obs_shape = space.shape
  
      if isinstance(
          space, (gym.spaces.Discrete, gym.spaces.MultiDiscrete)
      ):
          preprocessor = OneHotPreprocessor
      elif obs_shape == ATARI_OBS_SHAPE:
          logger.debug(
              "Defaulting to RLlib's GenericPixelPreprocessor because input "
              "space has the atari-typical shape {}. Turn this behaviour off by setting "
              "`preprocessor_pref=None` or "
              "`preprocessor_pref='deepmind'` or disabling the preprocessing API "
              "altogether with `_disable_preprocessor_api=True`.".format(
                  ATARI_OBS_SHAPE
              )
          )
          preprocessor = GenericPixelPreprocessor
      elif obs_shape == ATARI_RAM_OBS_SHAPE:
          logger.debug(
              "Defaulting to RLlib's AtariRamPreprocessor because input "
              "space has the atari-typical shape {}. Turn this behaviour off by setting "
              "`preprocessor_pref=None` or "
              "`preprocessor_pref='deepmind' or disabling the preprocessing API "
              "altogether with `_disable_preprocessor_api=True`."
              "`.".format(ATARI_OBS_SHAPE)
          )
          preprocessor = AtariRamPreprocessor
      elif isinstance(space, gym.spaces.Tuple):
          preprocessor = TupleFlatteningPreprocessor
      elif isinstance(space, gym.spaces.Dict):
          preprocessor = DictFlatteningPreprocessor
      elif isinstance(space, Repeated):
          preprocessor = RepeatedValuesPreprocessor
      # We usually only want to include this when using RLModules
      elif (
          isinstance(space, gym.spaces.MultiBinary)
          and include_multi_binary
      ):
          preprocessor = MultiBinaryPreprocessor
      else:
          preprocessor = NoPreprocessor
  
      return preprocessor
  
imports: from collections import OrderedDict
  import logging
  import numpy
  import gymnasium
  from typing import Any, List
  from ray.rllib.utils.annotations import override, PublicAPI, DeveloperAPI
  from ray.rllib.utils.spaces.repeated import Repeated
  from ray.rllib.utils.typing import TensorType
  from ray.rllib.utils.images import resize
  from ray.rllib.utils.spaces.space_utils import convert_element_to_space_type
label_desc: Use image node_id 1 for calling a global function with example usage: get_preprocessor(space, include_multi_binary) and returns: preprocessor