class_docstr: Callback for saving intermediate model checkpoints.
docstr: Initializes the callback.
  
  Args:
      checkpoint_dir: Directory to store checkpoints to.
docstr_tok: ["Initializes","the","callback",".","Args",":","checkpoint_dir",":","Directory","to","store","checkpoints","to","."]
code: def __init__(self, checkpoint_dir: Path) -> None:
      """Initializes the callback.
  
      Args:
          checkpoint_dir: Directory to store checkpoints to.
      """
      super().__init__()
  
      self.checkpoint_file = checkpoint_dir / "checkpoint.tf_model"
      self.best_metrics_so_far: Dict[Text, Any] = {}
  
file_path: rasa/rasa/utils/tensorflow/callback.py
imports: from pathlib import Path
  from typing import Dict, Text, Any, Optional
  import logging
  import tensorflow
  from tqdm import tqdm
  import rasa.shared.utils.io
label_desc: Use image node_id 1 to create a new RasaModelCheckpoint object from inherited base classes: tf.keras.callbacks with example: obj = RasaModelCheckpoint(checkpoint_dir)