See the guide: Training > Training Hooks
Saves checkpoints every N steps or seconds.
__init__( checkpoint_dir, save_secs=None, save_steps=None, saver=None, checkpoint_basename='model.ckpt', scaffold=None, listeners=None )
str, base directory for the checkpoint files.
int, save every N secs.
int, save every N steps.
Saverobject, used for saving.
str, base name for the checkpoint files.
Scaffold, use to get saver object.
listeners: List of
CheckpointSaverListenersubclass instances. Used for callbacks that run immediately before or after this hook saves the checkpoint.
ValueError: One of
save_secsshould be set.
ValueError: At most one of saver or scaffold should be set.
after_create_session( session, coord )
Called when new TensorFlow session is created.
This is called to signal the hooks that a new session has been created. This
has two essential differences with the situation in which
begin is called:
- When this is called, the graph is finalized and ops can no longer be added to the graph.
- This method will also be called as a result of recovering a wrapped session, not only at the beginning of the overall session.
session: A TensorFlow Session that has been created.
coord: A Coordinator object which keeps track of all threads.
after_run( run_context, run_values )