code: def device(self, device: int | str | torch.device | None):
      self._device, *_ = torch._C._nn._parse_to(device=device)
      if hasattr(self, "after_batch") and hasattr(
          self.after_batch, "fs"
      ):
          for tfm in self.after_batch.fs:
              # Check that tfm.to is callable as TabularPandas & transforms set tfm.to as an object
              if hasattr(tfm, "to") and callable(tfm.to):
                  tfm.to(device)
              else:
                  for a in L(getattr(tfm, "parameters", None)):
                      if hasattr(getattr(tfm, a), "to"):
                          setattr(tfm, a, getattr(tfm, a).to(device))
  
imports: from __future__ import annotations
  from ..torch_basics import *
  from torch.utils.data.dataloader import _MultiProcessingDataLoaderIter, _SingleProcessDataLoaderIter, _DatasetKind
label_desc: Use image node_id 9 for calling the DataLoader obj's underlying member method code with example usage: obj.device(device) without return types