code: def get_potential_fn(
      self, jit_compile=False, skip_jit_warnings=True, jit_options=None
  ):
      if jit_compile:
          jit_options = (
              {"check_trace": False}
              if jit_options is None
              else jit_options
          )
          return partial(
              self._potential_fn_jit, skip_jit_warnings, jit_options
          )
      return self._potential_fn
  
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 4 for calling the _PEMaker obj's underlying member method code with example usage: obj.get_potential_fn(jit_compile, skip_jit_warnings, jit_options) and returns: self, partial