class_docstr: `FGVC Aircraft <https://www.robots.ox.ac.uk/~vgg/data/fgvc-aircraft/>`_ Dataset.
  
  The dataset contains 10,000 images of aircraft, with 100 images for each of 100
  different aircraft model variants, most of which are airplanes.
  Aircraft models are organized in a three-levels hierarchy. The three levels, from
  finer to coarser, are:
  
  - ``variant``, e.g. Boeing 737-700. A variant collapses all the models that are visually
      indistinguishable into one class. The dataset comprises 100 different variants.
  - ``family``, e.g. Boeing 737. The dataset comprises 70 different families.
  - ``manufacturer``, e.g. Boeing. The dataset comprises 30 different manufacturers.
  
  Args:
      root (string): Root directory of the FGVC Aircraft dataset.
      split (string, optional): The dataset split, supports ``train``, ``val``,
          ``trainval`` and ``test``.
      annotation_level (str, optional): The annotation level, supports ``variant``,
          ``family`` and ``manufacturer``.
      transform (callable, optional): A function/transform that takes in a PIL image
          and returns a transformed version. E.g, ``transforms.RandomCrop``
      target_transform (callable, optional): A function/transform that takes in the
          target and transforms it.
      download (bool, optional): If True, downloads the dataset from the internet and
          puts it in root directory. If dataset is already downloaded, it is not
          downloaded again.
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docstr: Download the FGVC Aircraft dataset archive and extract it under root.
docstr_tok: ["Download","the","FGVC","Aircraft","dataset","archive","and","extract","it","under","root","."]
code: def _download(self) -> None:
      """
      Download the FGVC Aircraft dataset archive and extract it under root.
      """
      if self._check_exists():
          return
      download_and_extract_archive(self._URL, self.root)
  
file_path: vision/torchvision/datasets/fgvc_aircraft.py
imports: from __future__ import annotations
  import os
  from typing import Any, Callable, Optional, Tuple
  import PIL.Image
  from .utils import download_and_extract_archive, verify_str_arg
  from .vision import VisionDataset
label_desc: Use image node_id 4 for calling the FGVCAircraft obj's underlying member method code with example usage: obj._download() without return types