class_docstr: ``_WrappingCheckpointIO`` is a wrapper checkpoint_io that uses a base checkpoint_io to handle checkpointing.
  
  Args:
      checkpoint_io: A checkpoint IO plugin that is used as the basis.
class_docstr_tok: ["``","_WrappingCheckpointIO","``","is","a","wrapper","checkpoint_io","that","uses","a","base","checkpoint_io","to","handle","checkpointing",".","Args",":","checkpoint_io",":","A","checkpoint","IO","plugin","that","is","used","as","the","basis","."]
code: def __init__(
      self, checkpoint_io: Optional["CheckpointIO"] = None
  ) -> None:
      super().__init__()
  
      self._checkpoint_io = checkpoint_io
      self._base_checkpoint_io_configured: bool = False
  
      if checkpoint_io is not None:
          if isinstance(checkpoint_io, _WrappingCheckpointIO):
              self._base_checkpoint_io_configured = (
                  checkpoint_io._base_checkpoint_io_configured
              )
          else:
              self._base_checkpoint_io_configured = True
  
file_path: pytorch-lightning/src/lightning/pytorch/plugins/io/wrapper.py
imports: from typing import Any, Dict, Optional
  from typing_extensions import override
  from lightning.fabric.plugins import CheckpointIO
label_desc: Use image node_id 1 to create a new _WrappingCheckpointIO object from inherited base classes: CheckpointIO with example: obj = _WrappingCheckpointIO(checkpoint_io)