class_docstr: Vectorized Worker that collects partial episodes.
  
  Useful for off-policy RL.
  
  Args:
      seed (int): The seed to use to intialize random number generators.
      max_episode_length (int or float): The maximum length of episodes which
          will be sampled. Can be (floating point) infinity.
      length of fragments before they're transmitted out of
      worker_number (int): The number of the worker this update is
          occurring in. This argument is used to set a different seed for
          each worker.
      n_envs (int): Number of environment copies to use.
      timesteps_per_call (int): Maximum number of timesteps to gather per env
          per call to the worker. Defaults to 1 (i.e. gather 1 timestep per
          env each call, or n_envs timesteps in total each call).
docstr: Close the worker's environments.
docstr_tok: ["Close","the","worker","'s","environments","."]
code: def shutdown(self):
      """Close the worker's environments."""
      for env in self._envs:
          env.close()
  
file_path: garage/src/garage/sampler/fragment_worker.py
imports: import copy
  import numpy
  from garage import EpisodeBatch, StepType
  from garage.sampler import _apply_env_update, InProgressEpisode
  from garage.sampler.default_worker import DefaultWorker
label_desc: Use image node_id 7 for calling the FragmentWorker obj's underlying member method code with example usage: obj.shutdown() without return types