class_docstr: `Caltech 101 <https://data.caltech.edu/records/20086>`_ Dataset.
  
  .. warning::
  
      This class needs `scipy <https://docs.scipy.org/doc/>`_ to load target files from `.mat` format.
  
  Args:
      root (string): Root directory of dataset where directory
          ``caltech101`` exists or will be saved to if download is set to True.
      target_type (string or list, optional): Type of target to use, ``category`` or
          ``annotation``. Can also be a list to output a tuple with all specified
          target types.  ``category`` represents the target class, and
          ``annotation`` is a list of points from a hand-generated outline.
          Defaults to ``category``.
      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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code: def _check_integrity(self) -> bool:
      # can be more robust and check hash of files
      return os.path.exists(
          os.path.join(self.root, "101_ObjectCategories")
      )
  
imports: import os
  import os.path
  from typing import Any, Callable, List, Optional, Tuple, Union
  from PIL import Image
  from .utils import download_and_extract_archive, verify_str_arg
  from .vision import VisionDataset
label_desc: Use image node_id 3 for calling the Caltech101 obj's underlying member method code with example usage: obj._check_integrity() and returns: os