class_docstr: Interface to save/load checkpoints as they are saved through the ``Strategy``.
  
  .. warning::  This is an :ref:`experimental <versioning:Experimental API>` feature.
  
  Typically most plugins either use the Torch based IO Plugin; ``TorchCheckpointIO`` but may
  require particular handling depending on the plugin.
  
  In addition, you can pass a custom ``CheckpointIO`` by extending this class and passing it
  to the Trainer, i.e ``Trainer(plugins=[MyCustomCheckpointIO()])``.
  
  .. note::
  
      For some plugins, it is not possible to use a custom checkpoint plugin as checkpointing logic is not
      modifiable.
docstr: Save model/training states as a checkpoint file through state-dump and file-write.
  
  Args:
      checkpoint: dict containing model and trainer state
      path: write-target path
      storage_options: Optional parameters when saving the model/training states.
docstr_tok: ["Save","model\/training","states","as","a","checkpoint","file","through","state-dump","and","file-write",".","Args",":","checkpoint",":","dict","containing","model","and","trainer","state","path",":","write-target","path","storage_options",":","Optional","parameters","when","saving","the","model\/training","states","."]
code: def save_checkpoint(
      self,
      checkpoint: Dict[str, Any],
      path: _PATH,
      storage_options: Optional[Any] = None,
  ) -> None:
      """Save model/training states as a checkpoint file through state-dump and file-write.
  
      Args:
          checkpoint: dict containing model and trainer state
          path: write-target path
          storage_options: Optional parameters when saving the model/training states.
  
      """
  
file_path: pytorch-lightning/src/lightning/fabric/plugins/io/checkpoint_io.py
imports: from abc import ABC, abstractmethod
  from typing import Any, Dict, Optional
  from lightning.fabric.utilities.types import _PATH
label_desc: Use image node_id 1 for calling the CheckpointIO obj's underlying member method code with example usage: obj.save_checkpoint(checkpoint, path, storage_options) without return types