code: def test_multi_binary_preprocessor(self):
      observation_space = MultiBinary(5)
      # Firstly, exclude MultiBinary from the list of preprocessors.
      pp = ModelCatalog.get_preprocessor_for_space(
          observation_space, include_multi_binary=False
      )
      # Scondly, include MultiBinary with the list of preprocessors.
      self.assertTrue(isinstance(pp, NoPreprocessor))
      pp = ModelCatalog.get_preprocessor_for_space(
          observation_space, include_multi_binary=True
      )
      self.assertTrue(isinstance(pp, MultiBinaryPreprocessor))
      self.assertEqual(pp.observation_space.shape, (5,))
      check(pp.transform(np.array([0, 1, 0, 1, 1])), [0, 1, 0, 1, 1])
  
imports: import gymnasium
  from gymnasium.spaces import Box, Dict, Discrete, MultiDiscrete, Tuple, MultiBinary
  import numpy
  import unittest
  import ray
  import ray.rllib.algorithms.ppo
  from ray.rllib.models.catalog import ModelCatalog
  from ray.rllib.models.preprocessors import DictFlatteningPreprocessor, get_preprocessor, NoPreprocessor, TupleFlatteningPreprocessor, OneHotPreprocessor, AtariRamPreprocessor, GenericPixelPreprocessor, MultiBinaryPreprocessor
  from ray.rllib.utils.test_utils import check, check_compute_single_action, check_train_results, framework_iterator
  from ray.rllib.utils.framework import try_import_tf
label_desc: Use image node_id 7 for calling the TestPreprocessors obj's underlying member method code with example usage: obj.test_multi_binary_preprocessor() without return types