code: def test_tuple_preprocessor(self):
      class TupleEnv:
          def __init__(self):
              self.observation_space = Tuple(
                  [Discrete(5), Box(0, 5, shape=(3,), dtype=np.float32)]
              )
  
      pp = ModelCatalog.get_preprocessor(TupleEnv())
      self.assertTrue(isinstance(pp, TupleFlatteningPreprocessor))
      self.assertEqual(pp.shape, (8,))
      self.assertEqual(
          list(pp.transform((0, np.array([1, 2, 3], np.float32)))),
          [float(x) for x in [1, 0, 0, 0, 0, 1, 2, 3]],
      )
  
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 6 for calling the TestPreprocessors obj's underlying member method code with example usage: obj.test_tuple_preprocessor() without return types