class_docstr: Wrap a model `DataParallel` automatically
class_docstr_tok: ["Wrap","a","model","`","DataParallel","`","automatically"]
code: def after_fit(self):
      self.learn.model = self.learn.model.module
  
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 ParallelTrainer obj's underlying member method code with example usage: obj.after_fit() without return types