code: def get(env, property_name):
      if isinstance(env, batched_py_environment.BatchedPyEnvironment):
          assert env.batch_size == 1
          return getattr(env.envs[0], property_name)
      return getattr(env, property_name)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import threading
  from typing import Text
  from absl.testing import parameterized
  from absl.testing.absltest import mock
  import numpy
  import tensorflow
  from tf_agents import specs
  from tf_agents.environments import batched_py_environment
  from tf_agents.environments import py_environment
  from tf_agents.environments import suite_gym
  from tf_agents.environments import tf_py_environment
  from tf_agents.trajectories import time_step
  from tf_agents.utils import common
label_desc: Use image node_id 1 for calling a global function with example usage: get(env, property_name) and returns: getattr, getattr