code: def __init__(
      self,
      model,
      model_args,
      model_kwargs,
      trace_prob_evaluator,
      transforms,
  ):
      self.model = model
      self.model_args = model_args
      self.model_kwargs = model_kwargs
      self.trace_prob_evaluator = trace_prob_evaluator
      self.transforms = transforms
      self._compiled_fn = None
  
imports: import functools
  import traceback
  import warnings
  from collections import OrderedDict, defaultdict
  from functools import partial, reduce
  from itertools import product
  import torch
  from opt_einsum import shared_intermediates
  from torch.distributions import biject_to
  import pyro
  import pyro.poutine
  from pyro.distributions.util import broadcast_shape, logsumexp
  from pyro.infer import config_enumerate
  from pyro.infer.autoguide.initialization import InitMessenger, init_to_uniform
  from pyro.infer.util import is_validation_enabled
  from pyro.ops import stats
  from pyro.ops.contract import contract_to_tensor
  from pyro.ops.integrator import potential_grad
  from pyro.poutine.subsample_messenger import _Subsample
  from pyro.poutine.util import prune_subsample_sites
  from pyro.util import check_site_shape, ignore_jit_warnings
label_desc: Use image node_id 1 to create a new _PEMaker object  with example: obj = _PEMaker(model, model_args, model_kwargs, trace_prob_evaluator, transforms)