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 _prepare_sample(
      self, data: Tuple[np.ndarray, np.ndarray]
  ) -> Dict[str, Any]:
      image_array, label_array = data
  
      return dict(
          image=Image(image_array.transpose((2, 0, 1))),
          label=Label(
              int(label_array) % 10, categories=self._categories
          ),
      )
  
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 4 for calling the SVHN obj's underlying member method code with example usage: obj._prepare_sample(data) and returns: dict