class_docstr: EXPERIMENTAL Given a prefix of t-many observations, condition a (t+f)-long
  distribution on the observations, converting it to an f-long distribution.
  
  :param dict data: A dict mapping site name to tensors of observations.
class_docstr_tok: ["EXPERIMENTAL","Given","a","prefix","of","t-many","observations",",","condition","a","(","t+f",")","-long","distribution","on","the","observations",",","converting","it","to","an","f-long","distribution",".",":","param","dict","data",":","A","dict","mapping","site","name","to","tensors","of","observations","."]
code: def __init__(self, data):
      super().__init__()
      self.data = data
  
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 PrefixConditionMessenger object from inherited base classes: Messenger with example: obj = PrefixConditionMessenger(data)