class_docstr: Abstract base class for forecasting models.
  
  Derived classes must implement the :meth:`model` method.
class_docstr_tok: ["Abstract","base","class","for","forecasting","models",".","Derived","classes","must","implement","the",":","meth",":","`","model","`","method","."]
code: def __init__(self):
      super().__init__()
      self._prefix_condition_data = {}
  
imports: import logging
  from abc import ABCMeta, abstractmethod
  from contextlib import ExitStack
  import torch
  import torch.nn
  import pyro
  import pyro.distributions
  import pyro.poutine
  from pyro.infer import MCMC, NUTS, SVI, Trace_ELBO
  from pyro.infer.autoguide import AutoNormal, init_to_sample
  from pyro.infer.predictive import _guess_max_plate_nesting
  from pyro.nn.module import PyroModule
  from pyro.optim import DCTAdam
  from .util import MarkDCTParamMessenger, PrefixConditionMessenger, PrefixReplayMessenger, PrefixWarmStartMessenger, reshape_batch, time_reparam_dct, time_reparam_haar
label_desc: Use image node_id 1 to create a new ForecastingModel object from inherited base classes: PyroModule with example: obj = ForecastingModel()