code: def __new_init(self, loader, *args, **kwargs):
      self.__old_init__(loader, *args, **kwargs)
      if (
          hasattr(loader, "_speechbrain_recovery_skip_to")
          and loader._speechbrain_recovery_skip_to is not None
      ):
          # Fast forward the sampler iterator since we have recovered:
          for i in range(loader._speechbrain_recovery_skip_to):
              try:
                  next(self._sampler_iter)
              except StopIteration:
                  MSG = (
                      "Tried to fast-forward Sampler after checkpoint "
                  )
                  f"recovery by {loader._speechbrain_recovery_skip_to} "
                  "indices, but now Sampler raised StopIteration after "
                  f"{i} indices. Ignoring this mismatch."
                  warnings.warn(MSG)
                  break
              self._num_yielded = i + 1
          # Mark recovery as done:
          loader._speechbrain_recovery_skip_to = None
  
imports: from torch.utils.data import DataLoader
  from torch.utils.data import IterableDataset
  from torch.utils.data.dataloader import _BaseDataLoaderIter
  import logging
  import warnings
  import functools
  from torch.utils.data import DistributedSampler
  from speechbrain.dataio.batch import PaddedBatch, BatchsizeGuesser
  from speechbrain.dataio.dataset import DynamicItemDataset
  from speechbrain.dataio.sampler import ReproducibleRandomSampler, DistributedSamplerWrapper
  from speechbrain.utils.checkpoints import register_checkpoint_hooks, mark_as_saver, mark_as_loader
label_desc: Use image node_id 3 for calling a global function with example usage: __new_init(loader) without return types