code: def __iter__(self) -> Iterator[Tuple[int, int, int, int, int, str]]:
      for _, file in self.datapipe:
          data = read_mat(file, squeeze_me=True)
          for ann in data["annotations"]:
              yield tuple(ann)
  
imports: import pathlib
  from typing import Any, BinaryIO, Dict, Iterator, List, Tuple, Union
  from torchdata.datapipes.iter import Filter, IterDataPipe, Mapper, Zipper
  from torchvision.prototype.datasets.utils import Dataset, EncodedImage, HttpResource, OnlineResource
  from torchvision.prototype.datasets.utils._internal import hint_sharding, hint_shuffling, path_comparator, read_categories_file, read_mat
  from torchvision.prototype.tv_tensors import Label
  from torchvision.tv_tensors import BoundingBoxes
  from .._api import register_dataset, register_info
label_desc: Use image node_id 2 for calling the StanfordCarsLabelReader obj's underlying member method code with example usage: obj.__iter__() without return types