class_docstr: - **homepage**: https://github.com/facebookresearch/qmnist
class_docstr_tok: ["-","*","*","homepage","*","*",":","https",":","\/\/github.com\/facebookresearch\/qmnist"]
code: def __init__(
      self,
      root: Union[str, pathlib.Path],
      *,
      split: str = "train",
      skip_integrity_check: bool = False,
  ) -> None:
      self._split = self._verify_str_arg(
          split,
          "split",
          ("train", "test", "test10k", "test50k", "nist"),
      )
      super().__init__(root, skip_integrity_check=skip_integrity_check)
  
imports: import abc
  import functools
  import operator
  import pathlib
  import string
  from typing import Any, BinaryIO, cast, Dict, Iterator, List, Optional, Sequence, Tuple, Union
  import torch
  from torchdata.datapipes.iter import Decompressor, Demultiplexer, IterDataPipe, Mapper, Zipper
  from torchvision.prototype.datasets.utils import Dataset, HttpResource, OnlineResource
  from torchvision.prototype.datasets.utils._internal import hint_sharding, hint_shuffling, INFINITE_BUFFER_SIZE
  from torchvision.prototype.tv_tensors import Label
  from torchvision.prototype.utils._internal import fromfile
  from torchvision.tv_tensors import Image
  from .._api import register_dataset, register_info
label_desc: Use image node_id 1 to create a new QMNIST object from inherited base classes: _MNISTBase with example: obj = QMNIST(root)