class_docstr: Chainer extension to averagize persistents over workers.
  
  When called, this extension invokes all-reduce communication among
  workers to compute averages of persistent variables in the model.
  Persistent variables are updated to the averages. Currently, we ignore
  integer persistent variables, and only float persistent variables are
  handled.
  
  This extension is mainly to improve the running mean and variance of
  BatchNormalization by increasing the effective number of examples.
  We do not need to call this frequently; call just before storing or
  evaluating the model.
  
  Args:
      model (chainer.link.Link): Target link object.
      comm (ChainerMN communicator): communicator to compute averages.
code: def __init__(self, model, comm):
      self.model = model
      self.comm = comm
  
imports: import chainer
  import chainer.training.extension
label_desc: Use image node_id 1 to create a new AllreducePersistent object from inherited base classes: chainer.training.extension with example: obj = AllreducePersistent(model, comm)