class_docstr: Base class for experiment loggers.
class_docstr_tok: ["Base","class","for","experiment","loggers","."]
docstr: Called after model checkpoint callback saves a new checkpoint.
  
  Args:
      checkpoint_callback: the model checkpoint callback instance
docstr_tok: ["Called","after","model","checkpoint","callback","saves","a","new","checkpoint",".","Args",":","checkpoint_callback",":","the","model","checkpoint","callback","instance"]
code: def after_save_checkpoint(
      self, checkpoint_callback: ModelCheckpoint
  ) -> None:
      """Called after model checkpoint callback saves a new checkpoint.
  
      Args:
          checkpoint_callback: the model checkpoint callback instance
  
      """
      pass
  
imports: import functools
  import operator
  from abc import ABC
  from collections import defaultdict
  from typing import Any, Callable, Dict, Mapping, Optional, Sequence
  import numpy
  from typing_extensions import override
  from lightning.fabric.loggers import Logger
  from lightning.fabric.loggers.logger import _DummyExperiment
  from lightning.fabric.loggers.logger import rank_zero_experiment
  from lightning.pytorch.callbacks.model_checkpoint import ModelCheckpoint
label_desc: Use image node_id 1 for calling the Logger obj's underlying member method code with example usage: obj.after_save_checkpoint(checkpoint_callback) without return types