code: def get_action(self, s, greedy=False):  # run by a local
      s = s[np.newaxis, :]
      self.mu, self.sigma = self.actor(s)
  
      with tf.name_scope("wrap_a_out"):
          self.mu, self.sigma = self.mu * A_BOUND[1], self.sigma + 1e-5
      if greedy:
          return self.mu.numpy()[0]
      normal_dist = tfd.Normal(
          self.mu, self.sigma
      )  # for continuous action space
      self.A = tf.clip_by_value(
          tf.squeeze(normal_dist.sample(1), axis=0), *A_BOUND
      )
      return self.A.numpy()[0]
  
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 4 for calling the ACNet obj's underlying member method code with example usage: obj.get_action(s, greedy) and returns: self, self