code: def pull_global(
      self, globalAC
  ):  # run by a local, pull weights from the global nets
      for l_p, g_p in zip(
          self.actor.trainable_weights, globalAC.actor.trainable_weights
      ):
          l_p.assign(g_p)
      for l_p, g_p in zip(
          self.critic.trainable_weights,
          globalAC.critic.trainable_weights,
      ):
          l_p.assign(g_p)
  
imports: import argparse
  import multiprocessing
  import os
  import threading
  import time
  import gym
  import matplotlib.pyplot
  import numpy
  import tensorflow
  import tensorflow_probability
  import tensorlayer
label_desc: Use image node_id 3 for calling the ACNet obj's underlying member method code with example usage: obj.pull_global(globalAC) without return types