code: def get_cartpole_env_and_specs():
      env = suite_gym.load("CartPole-v0")
  
      (
          _,
          action_tensor_spec,
          time_step_tensor_spec,
      ) = spec_utils.get_tensor_specs(env)
  
      return env, action_tensor_spec, time_step_tensor_spec
  
imports: import functools
  from absl import logging
  import numpy
  import reverb
  import tensorflow
  from tf_agents.agents.dqn import dqn_agent
  from tf_agents.agents.ppo import ppo_clip_agent
  from tf_agents.environments import suite_gym
  from tf_agents.experimental.distributed import reverb_variable_container
  from tf_agents.networks import actor_distribution_network
  from tf_agents.networks import sequential
  from tf_agents.networks import value_network
  from tf_agents.policies import py_tf_eager_policy
  from tf_agents.replay_buffers import reverb_replay_buffer
  from tf_agents.specs import tensor_spec
  from tf_agents.train import actor
  from tf_agents.train.utils import replay_buffer_utils
  from tf_agents.train.utils import spec_utils
  from tf_agents.train.utils import train_utils
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
label_desc: Use image node_id 2 for calling a global function with example usage: get_cartpole_env_and_specs() and returns: env,  action_tensor_spec,  time_step_tensor_spec