class_docstr: Base class to define a dataset collection.
  
  Subclasses should overwrite `info` to return populated DatasetCollectionInfo.
  
  Subclasses should also overwrite `datasets` to return a dictionary of versions
  to the datasets included in that collection's version.
class_docstr_tok: ["Base","class","to","define","a","dataset","collection",".","Subclasses","should","overwrite","`","info","`","to","return","populated","DatasetCollectionInfo",".","Subclasses","should","also","overwrite","`","datasets","`","to","return","a","dictionary","of","versions","to","the","datasets","included","in","that","collection","'s","version","."]
docstr: Returns all versions available for the dataset collection.
docstr_tok: ["Returns","all","versions","available","for","the","dataset","collection","."]
code: def all_versions(self) -> List[version_lib.Version]:
      """Returns all versions available for the dataset collection."""
      return [
          version_lib.Version(version_str)
          for version_str in self.datasets.keys()
      ]
  
imports: import dataclasses
  import inspect
  from typing import Any, List, Mapping, Optional, Type, Union
  from etils import epath
  from tensorflow_datasets.core import naming
  from tensorflow_datasets.core import registered
  from tensorflow_datasets.core.utils import version
label_desc: Use image node_id 4 for calling the DatasetCollection obj's underlying member method code with example usage: obj.all_versions() and returns: unknown