code: def set_lr_mult(net, pattern, mult=1.0, verbose=False):
      """Reset lr_mult to new value for all parameters that match :obj:`pattern`
  
      Parameters
      ----------
      net : mxnet.gluon.Block
          The network whose parameters are going to be adjusted.
      pattern : str
          Regex matching pattern for targeting parameters.
      mult : float, default 1.0
          The new learning rate multiplier.
      verbose : bool
          Print which parameters being modified if set `True`.
  
      Returns
      -------
      mxnet.gluon.Block
          Original network with learning rate multipliers modified.
  
      """
      pattern = re.compile(pattern)
      for key, value in net.collect_params().items():
          if not re.match(pattern, key):
              continue
          value.lr_mult = mult
          if verbose:
              print("Set lr_mult of {} to {}".format(value.name, mult))
  
imports: import re
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: set_lr_mult(net, pattern, mult, verbose) without return types