class_docstr: An inductive dataset that has lazy loading.
class_docstr_tok: ["An","inductive","dataset","that","has","lazy","loading","."]
docstr: Get the appropriate cache root directory.
  
  :param cache_root: If none is passed, defaults to a subfolder of the
      PyKEEN home directory defined in :data:`pykeen.constants.PYKEEN_HOME`.
      The subfolder is named based on the class inheriting from
      :class:`pykeen.datasets.base.Dataset`.
  :param version: accepts a string "v1" to "v4" to select among Teru et al inductive datasets
  :param sep_train_inference: a flag to store training and inference splits in different folders
  :returns: A path object for the calculated cache root directory
docstr_tok: ["Get","the","appropriate","cache","root","directory",".",":","param","cache_root",":","If","none","is","passed",",","defaults","to","a","subfolder","of","the","PyKEEN","home","directory","defined","in",":","data",":","`","pykeen.constants.PYKEEN_HOME","`",".","The","subfolder","is","named","based","on","the","class","inheriting","from",":","class",":","`","pykeen.datasets.base.Dataset","`",".",":","param","version",":","accepts","a","string","``","v1","''","to","``","v4","''","to","select","among","Teru","et","al","inductive","datasets",":","param","sep_train_inference",":","a","flag","to","store","training","and","inference","splits","in","different","folders",":","returns",":","A","path","object","for","the","calculated","cache","root","directory"]
code: def _help_cache(
      self,
      cache_root: Union[None, str, pathlib.Path],
      version: Optional[str] = None,
      sep_train_inference: bool = False,
  ) -> pathlib.Path:
      """Get the appropriate cache root directory.
  
      :param cache_root: If none is passed, defaults to a subfolder of the
          PyKEEN home directory defined in :data:`pykeen.constants.PYKEEN_HOME`.
          The subfolder is named based on the class inheriting from
          :class:`pykeen.datasets.base.Dataset`.
      :param version: accepts a string "v1" to "v4" to select among Teru et al inductive datasets
      :param sep_train_inference: a flag to store training and inference splits in different folders
      :returns: A path object for the calculated cache root directory
      """
      cache_root = normalize_path(
          cache_root,
          *self._cache_sub_directories(version=version),
          default=PYKEEN_DATASETS,
          mkdir=True,
      )
      if sep_train_inference:
          # generate subfolders 'training' and  'inference'
          for name in ("training", "inference"):
              cache_root.joinpath(name).mkdir(
                  parents=True, exist_ok=True
              )
      logger.debug("using cache root at %s", cache_root.as_uri())
      return cache_root
  
imports: from __future__ import annotations
  import logging
  import pathlib
  from dataclasses import dataclass
  from typing import Any, Iterable, Mapping, Optional, Union
  from pystow.utils import download, name_from_url
  from tabulate import tabulate
  from ...constants import PYKEEN_DATASETS
  from ...triples import CoreTriplesFactory, TriplesFactory
  from ...utils import normalize_path
label_desc: Use image node_id 8 for calling the LazyInductiveDataset obj's underlying member method code with example usage: obj._help_cache(cache_root, version, sep_train_inference) and returns: cache_root