code: def factor(
      name: str,
      log_factor: torch.Tensor,
      *,
      has_rsample: Optional[bool] = None,
  ) -> None:
      """
      Factor statement to add arbitrary log probability factor to a
      probabilisitic model.
  
      .. warning:: When using factor statements in guides, you'll need to specify
          whether the factor statement originated from fully reparametrized
          sampling (e.g. the Jacobian determinant of a transformation of a
          reparametrized variable) or from nonreparameterized sampling (e.g.
          discrete samples). For the fully reparametrized case, set
          ``has_rsample=True``; for the nonreparametrized case, set
          ``has_rsample=False``. This is needed only in guides, not in models.
  
      :param str name: Name of the trivial sample
      :param torch.Tensor log_factor: A possibly batched log probability factor.
      :param bool has_rsample: Whether the ``log_factor`` arose from a fully
          reparametrized distribution. Defaults to False when used in models, but
          must be specified for use in guides.
      """
      unit_dist = dist.Unit(log_factor, has_rsample=has_rsample)
      unit_value = unit_dist.sample()
      sample(
          name, unit_dist, obs=unit_value, infer={"is_auxiliary": True}
      )
  
imports: import copy
  import warnings
  from collections import OrderedDict
  from contextlib import ExitStack, contextmanager
  from inspect import isclass
  from typing import Callable, Iterator, Optional, Sequence, Union
  import torch
  from torch.distributions import constraints
  import pyro.distributions
  import pyro.infer
  import pyro.poutine
  from pyro.distributions.torch_distribution import TorchDistributionMixin
  from pyro.params import param_with_module_name
  from pyro.params.param_store import ParamStoreDict
  from pyro.poutine.plate_messenger import PlateMessenger
  from pyro.poutine.runtime import _MODULE_NAMESPACE_DIVIDER, _PYRO_PARAM_STORE, InferDict, Message, am_i_wrapped, apply_stack, effectful
  from pyro.poutine.subsample_messenger import SubsampleMessenger
  from pyro.util import deep_getattr, set_rng_seed
label_desc: Use image node_id 6 for calling a global function with example usage: factor(name, log_factor) without return types