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. (deprecated)
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 inall_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 akeep_checkpoint_every_n_hours
parameter (seetf.contrib.checkpoint.CheckpointManager
for an implementation).
Raises:
RuntimeError
: If any of the model checkpoint paths conflict with the file containing CheckpointSate.