class_docstr: A Worker object is created for each training thread.
class_docstr_tok: ["A","Worker","object","is","created","for","each","training","thread","."]
code: def __init__(self, ppo, index):
      self.ppo = ppo
      self.index = index
      self.scope = "worker%d" % index
      self.env = copy.deepcopy(ppo._env)
      self.env.reset()
      self.model = ppo._build_model(None)
      self.rnn_states = ppo._policy.rnn_initial_states
  
imports: import copy
  import time
  from collections.abc import Sequence
  from multiprocessing.dummy import Pool
  import numpy
  import tensorflow
  from deepchem.models import KerasModel
  from deepchem.models.optimizers import Adam
label_desc: Use image node_id 1 to create a new _Worker object from inherited base classes: object with example: obj = _Worker(ppo, index)