code: def __init__(
      self,
      root: Union[str, pathlib.Path],
      *,
      skip_integrity_check: bool = False,
      dependencies: Collection[str] = (),
  ) -> None:
      for dependency in dependencies:
          try:
              importlib.import_module(dependency)
          except ModuleNotFoundError:
              raise ModuleNotFoundError(
                  f"{type(self).__name__}() depends on the third-party package '{dependency}'. "
                  f"Please install it, for example with `pip install {dependency}`."
              ) from None
  
      self._root = pathlib.Path(root).expanduser().resolve()
      resources = [
          resource.load(
              self._root, skip_integrity_check=skip_integrity_check
          )
          for resource in self._resources()
      ]
      self._dp = self._datapipe(resources)
  
file_path: vision/torchvision/prototype/datasets/utils/_dataset.py
imports: import abc
  import importlib
  import pathlib
  from typing import Any, Collection, Dict, Iterator, List, Optional, Sequence, Union
  from torchdata.datapipes.iter import IterDataPipe
  from torchvision.datasets.utils import verify_str_arg
  from ._resource import OnlineResource
label_desc: Use image node_id 2 to create a new Dataset object from inherited base classes: IterDataPipe, abc with example: obj = Dataset(root)