class_docstr: SVHN Dataset.
  homepage="http://ufldl.stanford.edu/housenumbers/",
  dependencies = scipy
class_docstr_tok: ["SVHN","Dataset",".","homepage=","''","http",":","\/\/ufldl.stanford.edu\/housenumbers\/","''",",","dependencies","=","scipy"]
code: def _read_images_and_labels(
      self, data: Tuple[str, BinaryIO]
  ) -> List[Tuple[np.ndarray, np.ndarray]]:
      _, buffer = data
      content = read_mat(buffer)
      return list(
          zip(
              content["X"].transpose((3, 0, 1, 2)),
              content["y"].squeeze(),
          )
      )
  
file_path: vision/torchvision/prototype/datasets/_builtin/svhn.py
imports: import pathlib
  from typing import Any, BinaryIO, Dict, List, Tuple, Union
  import numpy
  from torchdata.datapipes.iter import IterDataPipe, Mapper, UnBatcher
  from torchvision.prototype.datasets.utils import Dataset, HttpResource, OnlineResource
  from torchvision.prototype.datasets.utils._internal import hint_sharding, hint_shuffling, read_mat
  from torchvision.prototype.tv_tensors import Label
  from torchvision.tv_tensors import Image
  from .._api import register_dataset, register_info
label_desc: Use image node_id 3 for calling the SVHN obj's underlying member method code with example usage: obj._read_images_and_labels(data) and returns: list