code: def test_nested_multidiscrete_one_hot_preprocessor(self):
      space = Tuple((MultiDiscrete([2, 3, 4]),))
      pp = get_preprocessor(space)(space)
      self.assertTrue(pp.shape == (9,))
      check(
          pp.transform((np.array([1, 2, 0]),)),
          [0.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 0.0],
      )
      check(
          pp.transform((np.array([0, 1, 3]),)),
          [1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0],
      )
  
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 10 for calling the TestPreprocessors obj's underlying member method code with example usage: obj.test_nested_multidiscrete_one_hot_preprocessor() without return types