tf.train.MonitoredTrainingSession

tf.train.MonitoredTrainingSession

tf.train.MonitoredTrainingSession

MonitoredTrainingSession(
    master='',
    is_chief=True,
    checkpoint_dir=None,
    scaffold=None,
    hooks=None,
    chief_only_hooks=None,
    save_checkpoint_secs=600,
    save_summaries_steps=100,
    save_summaries_secs=None,
    config=None,
    stop_grace_period_secs=120,
    log_step_count_steps=100
)

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

See the guide: Training > Distributed execution

Creates a MonitoredSession for training.

For a chief, this utility sets proper session initializer/restorer. It also creates hooks related to checkpoint and summary saving. For workers, this utility sets proper session creator which waits for the chief to initialize/restore.

Args:

• master: String the TensorFlow master to use.
• is_chief: If True, it will take care of initialization and recovery the underlying TensorFlow session. If False, it will wait on a chief to initialize or recover the TensorFlow session.
• checkpoint_dir: A string. Optional path to a directory where to restore variables.
• scaffold: A Scaffold used for gathering or building supportive ops. If not specified, a default one is created. It's used to finalize the graph.
• hooks: Optional list of SessionRunHook objects.
• chief_only_hooks: list of SessionRunHook objects. Activate these hooks if is_chief==True, ignore otherwise.
• save_checkpoint_secs: The frequency, in seconds, that a checkpoint is saved using a default checkpoint saver. If save_checkpoint_secs is set to None, then the default checkpoint saver isn't used.
• save_summaries_steps: The frequency, in number of global steps, that the summaries are written to disk using a default summary saver. If both save_summaries_steps and save_summaries_secs are set to None, then the default summary saver isn't used.
• save_summaries_secs: The frequency, in secs, that the summaries are written to disk using a default summary saver. If both save_summaries_steps and save_summaries_secs are set to None, then the default summary saver isn't used.
• config: an instance of tf.ConfigProto proto used to configure the session. It's the config argument of constructor of tf.Session.
• stop_grace_period_secs: Number of seconds given to threads to stop after close() has been called.
• log_step_count_steps: The frequency, in number of global steps, that the global step/sec is logged.

Returns:

A MonitoredSession object.