class_docstr: Wrap a model `DataParallel` automatically
class_docstr_tok: ["Wrap","a","model","`","DataParallel","`","automatically"]
code: def __init__(self, device_ids):
      self.device_ids = device_ids
  
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 1 to create a new ParallelTrainer object from inherited base classes: Callback with example: obj = ParallelTrainer(device_ids)