class_docstr: A `TfmdDL` which splits a batch into equal size pieces for each worker
class_docstr_tok: ["A","`","TfmdDL","`","which","splits","a","batch","into","equal","size","pieces","for","each","worker"]
code: def _to_detach(self, b, cpu=True, gather=True):
      return to_detach(b, cpu, gather)
  
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 DistributedDL obj's underlying member method code with example usage: obj._to_detach(b, cpu, gather) and returns: to_detach