class_docstr: Defines an abstract observation preprocessor function.
  
  Attributes:
      shape (List[int]): Shape of the preprocessed output.
code: def __init__(self, obs_space: gym.Space, options: dict = None):
      _legacy_patch_shapes(obs_space)
      self._obs_space = obs_space
      if not options:
          from ray.rllib.models.catalog import MODEL_DEFAULTS
  
          self._options = MODEL_DEFAULTS.copy()
      else:
          self._options = options
      self.shape = self._init_shape(obs_space, self._options)
      self._size = int(np.product(self.shape))
      self._i = 0
      self._obs_for_type_matching = self._obs_space.sample()
  
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 to create a new Preprocessor object  with example: obj = Preprocessor(obs_space, options)