code: def collect_demonstrations(
      agent,
      env,
      steps,
      episodes,
      outdir,
      max_episode_len=None,
      logger=None,
  ):
      """Collects demonstrations from an agent and writes them to a file.
  
      Args:
          agent: Agent from which demonstrations are collected.
          env: Environment in which the agent produces demonstrations.
          steps (int): Number of total time steps to collect demonstrations for.
          episodes (int): Number of total episodes to collect demonstrations for.
          outdir (str): Path to the directory to output demonstrations.
          max_episode_len (int): Maximum episode length.
          logger (logging.Logger): Logger used in this function.
      """
      assert (steps is None) != (episodes is None)
      logger = logger or logging.getLogger(__name__)
  
      with chainer.datasets.open_pickle_dataset_writer(
          os.path.join(outdir, "demos.pickle")
      ) as dataset:
          # o_0, r_0
          terminate = False  # True if we should stop collecting demos
          timestep = 0  # number of timesteps of demos collected
          episode_num = 0  # number of episodes of demos collected
          episode_len = 0  # length of most recent episode
          reset = True  # whether to reset environment
          episode_r = 0  # Episode reward
          while not terminate:
              if reset:
                  if episode_num > 0:
                      logger.info(
                          "demonstration episode %s length:%s R:%s",
                          episode_num,
                          episode_len,
                          episode_r,
                      )
                  obs = env.reset()
                  done = False
                  r = 0
                  episode_r = 0
                  episode_len = 0
                  info = {}
              # a_t
              a = agent.act(obs)
              # o_{t+1}, r_{t+1}
              new_obs, r, done, info = env.step(a)
              # o_t, a_t, r__{t+1}, o_{t+1}
              dataset.write((obs, a, r, new_obs, done, info))
              obs = new_obs
              reset = (
                  done
                  or episode_len == max_episode_len
                  or info.get("needs_reset", False)
              )
              timestep += 1
              episode_len += 1
              episode_r += r
              episode_num = episode_num + 1 if reset else episode_num
              if steps is None:
                  terminate = episode_num >= episodes
              else:
                  terminate = timestep >= steps
              if reset or terminate:
                  agent.stop_episode()
                  if terminate:
                      # log final episode
                      logger.info(
                          "demonstration episode %s length:%s R:%s",
                          episode_num,
                          episode_len,
                          episode_r,
                      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: collect_demonstrations(agent, env, steps, episodes, outdir, max_episode_len, logger) without return types