class_docstr: Initialize a worker.
  
  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.
      worker_number (int): The number of the worker where this update is
          occurring. This argument is used to set a different seed for each
          worker.
  
  Attributes:
      agent (Policy or None): The worker's agent.
      env (Environment or None): The worker's environment.
class_docstr_tok: ["Initialize","a","worker",".","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",".","worker_number","(","int",")",":","The","number","of","the","worker","where","this","update","is","occurring",".","This","argument","is","used","to","set","a","different","seed","for","each","worker",".","Attributes",":","agent","(","Policy","or","None",")",":","The","worker","'s","agent",".","env","(","Environment","or","None",")",":","The","worker","'s","environment","."]
docstr: Initialize a worker.
docstr_tok: ["Initialize","a","worker","."]
code: def worker_init(self):
      """Initialize a worker."""
      if self._seed is not None:
          deterministic.set_seed(self._seed + self._worker_number)
  
file_path: garage/src/garage/sampler/default_worker.py
imports: from collections import defaultdict
  import numpy
  from garage import EpisodeBatch, StepType
  from garage.experiment import deterministic
  from garage.sampler import _apply_env_update
  from garage.sampler.worker import Worker
label_desc: Use image node_id 2 for calling the DefaultWorker obj's underlying member method code with example usage: obj.worker_init() without return types