class_docstr: DDPG class
class_docstr_tok: ["DDPG","class"]
docstr: Soft updating by exponential smoothing
  :return: None
docstr_tok: ["Soft","updating","by","exponential","smoothing",":","return",":","None"]
code: def ema_update(self):
      """
      Soft updating by exponential smoothing
      :return: None
      """
      paras = (
          self.actor.trainable_weights + self.critic.trainable_weights
      )
      self.ema.apply(paras)
      for i, j in zip(
          self.actor_target.trainable_weights
          + self.critic_target.trainable_weights,
          paras,
      ):
          i.assign(self.ema.average(j))
  
file_path: TensorLayer/examples/reinforcement_learning/tutorial_DDPG.py
imports: import argparse
  import os
  import time
  import gym
  import matplotlib.pyplot
  import numpy
  import tensorflow
  import tensorlayer
label_desc: Use image node_id 2 for calling the DDPG obj's underlying member method code with example usage: obj.ema_update() without return types