code: def to_parallel(self: Learner, device_ids=None):
      "Add `ParallelTrainer` callback to a `Learner`"
      self.add_cb(ParallelTrainer(device_ids))
      return self
  
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 2 for calling a global function with example usage: to_parallel(device_ids) and returns: self