tf.train.update_checkpoint_state

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

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

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'.
  • all_model_checkpoint_timestamps: Optional list of timestamps (floats, seconds since the Epoch) indicating when the checkpoints in all_model_checkpoint_paths were created.
  • last_preserved_timestamp: A float, indicating the number of seconds since the Epoch when the last preserved checkpoint was written, e.g. due to a keep_checkpoint_every_n_hours parameter (see tf.contrib.checkpoint.CheckpointManager for an implementation).

Raises:

  • RuntimeError: If any of the model checkpoint paths conflict with the file containing CheckpointSate.