code: def get_target_updates(_vars, target_vars, tau, verbose=0):
      """
      get target update operations
  
      :param _vars: ([TensorFlow Tensor]) the initial variables
      :param target_vars: ([TensorFlow Tensor]) the target variables
      :param tau: (float) the soft update coefficient (keep old values, between 0 and 1)
      :param verbose: (int) the verbosity level: 0 none, 1 training information, 2 tensorflow debug
      :return: (TensorFlow Operation, TensorFlow Operation) initial update, soft update
      """
      if verbose >= 2:
          logger.info("setting up target updates ...")
      soft_updates = []
      init_updates = []
      assert len(_vars) == len(target_vars)
      for var, target_var in zip(_vars, target_vars):
          if verbose >= 2:
              logger.info(
                  "  {} <- {}".format(target_var.name, var.name)
              )
          init_updates.append(tf.assign(target_var, var))
          soft_updates.append(
              tf.assign(
                  target_var, (1.0 - tau) * target_var + tau * var
              )
          )
      assert len(init_updates) == len(_vars)
      assert len(soft_updates) == len(_vars)
      return tf.group(*init_updates), tf.group(*soft_updates)
  
imports: from functools import reduce
  import os
  import time
  from collections import deque
  import pickle
  import warnings
  import gym
  import numpy
  import tensorflow
  import tensorflow.contrib
  from mpi4py import MPI
  from stable_baselines import logger
  from stable_baselines.common import tf_util, OffPolicyRLModel, SetVerbosity, TensorboardWriter
  from stable_baselines.common.vec_env import VecEnv
  from stable_baselines.common.mpi_adam import MpiAdam
  from stable_baselines.common.buffers import ReplayBuffer
  from stable_baselines.common.math_util import unscale_action, scale_action
  from stable_baselines.common.mpi_running_mean_std import RunningMeanStd
  from stable_baselines.ddpg.policies import DDPGPolicy
label_desc: Use image node_id 5 for calling a global function with example usage: get_target_updates(_vars, target_vars, tau, verbose) and returns: tf,  tf