class_docstr: Wrap `model` in `DistributedDataParallel` and `dls` in `DistributedDL`
class_docstr_tok: ["Wrap","`","model","`","in","`","DistributedDataParallel","`","and","`","dls","`","in","`","DistributedDL","`"]
code: def _wrap_dl(self, dl):
      return (
          dl
          if isinstance(dl, DistributedDL)
          else DistributedDL(dl, device=self.learn.model.device)
      )
  
imports: from __future__ import annotations
  from .basics import *
  from .callback.progress import ProgressCallback
  from torch.nn.parallel import DistributedDataParallel, DataParallel
  from .data.load import _FakeLoader, _loaders
  from .optimizer import OptimWrapper
label_desc: Use image node_id 3 for calling the DistributedTrainer obj's underlying member method code with example usage: obj._wrap_dl(dl) and returns: unknown