class_docstr: Worker class for distributional running
class_docstr_tok: ["Worker","class","for","distributional","running"]
code: def __init__(self, wid):
      self.wid = wid
      self.env = gym.make(ENV_ID).unwrapped
      self.env.seed(wid * 100 + RANDOMSEED)
      self.ppo = GLOBAL_PPO
  
imports: import argparse
  import os
  import queue
  import threading
  import time
  import gym
  import matplotlib.pyplot
  import numpy
  import tensorflow
  import tensorflow_probability
  import tensorlayer
label_desc: Use image node_id 1 to create a new Worker object from inherited base classes: object with example: obj = Worker(wid)