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) -> None:
      """Called after model checkpoint callback saves a new checkpoint.
  
      Args:
          checkpoint_callback: the model checkpoint callback instance
      """
      self.checkpoint_path = checkpoint_callback.best_model_path
  
file_path: neural_prophet/neuralprophet/logger.py
imports: import collections
  from typing import Any, Mapping, Optional
  import pytorch_lightning
  from pytorch_lightning.callbacks import TQDMProgressBar
  from pytorch_lightning.loggers import TensorBoardLogger
  from pytorch_lightning.utilities.rank_zero import rank_zero_only
label_desc: Use image node_id 2 for calling the MetricsLogger obj's underlying member method code with example usage: obj.after_save_checkpoint(checkpoint_callback) without return types