code: def moving_average(net1, net2, alpha=1):
      for param1, param2 in zip(net1.parameters(), net2.parameters()):
          param1.data *= 1.0 - alpha
          param1.data += param2.data * alpha
  
file_path: insightface/parsing/dml_csr/utils/schp.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: moving_average(net1, net2, alpha) without return types