code: def __iter__(self):
      if self.dataloader.sampler is not None and isinstance(
          self.dataloader.sampler,
          torch.utils.data.distributed.DistributedSampler,
      ):
          self.dataloader.sampler.set_epoch(self.epoch)
      self.epoch += 1
      return PrefetchedWrapper.prefetched_loader(
          self.dataloader, self.num_classes, self.one_hot
      )
  
imports: import os
  import torch
  import numpy
  from PIL import Image
  from functools import partial
  from image_classification.autoaugment import AutoaugmentImageNetPolicy
  import torchvision.datasets
  import torchvision.transforms
label_desc: Use image node_id 3 for calling the PrefetchedWrapper obj's underlying member method code with example usage: obj.__iter__() and returns: PrefetchedWrapper