tf.train.update_checkpoint_state(save_dir, model_checkpoint_path, all_model_checkpoint_paths=None, latest_filename=None)

tf.train.update_checkpoint_state(save_dir, model_checkpoint_path, all_model_checkpoint_paths=None, latest_filename=None)

See the guide: Variables > Saving and Restoring Variables

Updates the content of the 'checkpoint' file.

This updates the checkpoint file containing a CheckpointState proto.

Args:

  • save_dir: Directory where the model was saved.
  • model_checkpoint_path: The checkpoint file.
  • all_model_checkpoint_paths: List of strings. Paths to all not-yet-deleted checkpoints, sorted from oldest to newest. If this is a non-empty list, the last element must be equal to model_checkpoint_path. These paths are also saved in the CheckpointState proto.
  • latest_filename: Optional name of the checkpoint file. Default to 'checkpoint'.

Raises:

  • RuntimeError: If the save paths conflict.

Defined in tensorflow/python/training/saver.py.