code: def __getitem__(self, index):
      item = self.dataset[index]
      image = item[self.image_key]
      if "bytes" in image and image["bytes"]:
          image = io.BytesIO(image["bytes"])
      else:
          assert "path" in image and image["path"]
          image = open(image["path"], "rb")
      label = item[self.label_key]
      if self.remap_class:
          label = self.class_to_idx[label]
      return image, label
  
file_path: pytorch-image-models/timm/data/readers/reader_hfds.py
imports: import io
  import math
  from typing import Optional
  import torch
  import torch.distributed
  from PIL import Image
  from .class_map import load_class_map
  from .reader import Reader
label_desc: Use image node_id 2 for calling the ReaderHfds obj's underlying member method code with example usage: obj.__getitem__(index) and returns: image,  label