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 the latest version of this dataset collection.
docstr_tok: ["Returns","the","latest","version","of","this","dataset","collection","."]
code: def get_latest_version(self) -> str:
      """Returns the latest version of this dataset collection."""
      return str(max(self.all_versions))
  
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 5 for calling the DatasetCollection obj's underlying member method code with example usage: obj.get_latest_version() and returns: str