class_docstr: Hooks to be used with Checkpointing.
class_docstr_tok: ["Hooks","to","be","used","with","Checkpointing","."]
docstr: Called by Lightning when saving a checkpoint to give you a chance to store anything else you might want to
  save.
  
  Args:
      checkpoint: The full checkpoint dictionary before it gets dumped to a file.
          Implementations of this hook can insert additional data into this dictionary.
  
  Example::
  
      def on_save_checkpoint(self, checkpoint):
          # 99% of use cases you don't need to implement this method
          checkpoint['something_cool_i_want_to_save'] = my_cool_pickable_object
  
  Note:
      Lightning saves all aspects of training (epoch, global step, etc...)
      including amp scaling.
      There is no need for you to store anything about training.
code: def on_save_checkpoint(self, checkpoint: Dict[str, Any]) -> None:
      r"""Called by Lightning when saving a checkpoint to give you a chance to store anything else you might want to
      save.
  
      Args:
          checkpoint: The full checkpoint dictionary before it gets dumped to a file.
              Implementations of this hook can insert additional data into this dictionary.
  
      Example::
  
          def on_save_checkpoint(self, checkpoint):
              # 99% of use cases you don't need to implement this method
              checkpoint['something_cool_i_want_to_save'] = my_cool_pickable_object
  
      Note:
          Lightning saves all aspects of training (epoch, global step, etc...)
          including amp scaling.
          There is no need for you to store anything about training.
  
      """
  
imports: from typing import Any, Dict, Optional
  import torch
  from torch import Tensor
  from torch.optim.optimizer import Optimizer
  from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_0
  from lightning.pytorch.utilities import move_data_to_device
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.types import EVAL_DATALOADERS, STEP_OUTPUT, TRAIN_DATALOADERS
label_desc: Use image node_id 2 for calling the CheckpointHooks obj's underlying member method code with example usage: obj.on_save_checkpoint(checkpoint) without return types