class_docstr: Swiss army knife of broadcasting amazingness:
  combines shape inference, independence annotation, and subsampling
code: def __enter__(self) -> Optional["torch.Tensor"]:  # type: ignore[override]
      super().__enter__()
      if self._vectorized and self._indices is not None:
          return self.indices
      return None
  
file_path: pyro/pyro/poutine/plate_messenger.py
imports: from contextlib import contextmanager
  from typing import TYPE_CHECKING, Iterator, Optional
  from pyro.poutine.broadcast_messenger import BroadcastMessenger
  from pyro.poutine.messenger import Messenger, block_messengers
  from pyro.poutine.subsample_messenger import SubsampleMessenger
label_desc: Use image node_id 2 for calling the PlateMessenger obj's underlying member method code with example usage: obj.__enter__() and returns: None, self