class_docstr: EXPERIMENTAL Given a trace of training data, replay a model with batched
  sites extended to include both training and forecast time, using the guide
  trace for the training prefix and samples from the prior on the forecast
  postfix.
  
  :param trace: a guide trace.
  :type trace: ~pyro.poutine.trace_struct.Trace
class_docstr_tok: ["EXPERIMENTAL","Given","a","trace","of","training","data",",","replay","a","model","with","batched","sites","extended","to","include","both","training","and","forecast","time",",","using","the","guide","trace","for","the","training","prefix","and","samples","from","the","prior","on","the","forecast","postfix",".",":","param","trace",":","a","guide","trace",".",":","type","trace",":","~pyro.poutine.trace_struct.Trace"]
code: def __init__(self, trace):
      super().__init__()
      self.trace = trace
  
imports: import numbers
  from functools import singledispatch
  import torch
  from torch.distributions import transform_to, transforms
  import pyro.distributions
  from pyro.infer.reparam import DiscreteCosineReparam, HaarReparam
  from pyro.poutine.messenger import Messenger
  from pyro.poutine.util import site_is_subsample
  from pyro.primitives import get_param_store
label_desc: Use image node_id 1 to create a new PrefixReplayMessenger object from inherited base classes: Messenger with example: obj = PrefixReplayMessenger(trace)