class_docstr: `SVHN <http://ufldl.stanford.edu/housenumbers/>`_ Dataset.
  Note: The SVHN dataset assigns the label `10` to the digit `0`. However, in this Dataset,
  we assign the label `0` to the digit `0` to be compatible with PyTorch loss functions which
  expect the class labels to be in the range `[0, C-1]`
  
  .. warning::
  
      This class needs `scipy <https://docs.scipy.org/doc/>`_ to load data from `.mat` format.
  
  Args:
      root (string): Root directory of the dataset where the data is stored.
      split (string): One of {'train', 'test', 'extra'}.
          Accordingly dataset is selected. 'extra' is Extra training set.
      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.
code: def __len__(self) -> int:
      return len(self.data)
  
file_path: vision/torchvision/datasets/svhn.py
imports: import os.path
  from typing import Any, Callable, Optional, Tuple
  import numpy
  from PIL import Image
  from .utils import check_integrity, download_url, verify_str_arg
  from .vision import VisionDataset
label_desc: Use image node_id 3 for calling the SVHN obj's underlying member method code with example usage: obj.__len__() and returns: len