code: def soft_copy_params(source, target, tau):
      """Make the parameters of a link close to the ones of another link.
  
      Making tau close to 0 slows the pace of updates, and close to 1 might lead
      to faster, but more volatile updates.
      """
      # Sort params by name
      source_params = [
          param for _, param in sorted(source.namedparams())
      ]
      target_params = [
          param for _, param in sorted(target.namedparams())
      ]
      for s, t in zip(source_params, target_params):
          t.array[:] += tau * (s.array - t.array)
  
imports: from __future__ import division
  import argparse
  import collections
  import copy
  import random
  import warnings
  import gym
  import numpy
  import chainer
  from chainer import functions
  from chainer import links
  from chainer import optimizers
label_desc: Use image node_id 4 for calling a global function with example usage: soft_copy_params(source, target, tau) without return types