code: def __init__(
      self,
      d,
      pin_memory,
      num_workers,
      timeout,
      persistent_workers,
      pin_memory_device,
  ):
      (
          self.dataset,
          self.default,
          self.worker_init_fn,
          self.pin_memory_device,
      ) = (self, d, _wif, pin_memory_device)
      store_attr(
          "d,pin_memory,num_workers,timeout,persistent_workers,pin_memory_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 2 to create a new _FakeLoader object  with example: obj = _FakeLoader(d, pin_memory, num_workers, timeout, persistent_workers, pin_memory_device)