MonitoredTrainingSession(
master='',
is_chief=True,
checkpoint_dir=None,
scaffold=None,
hooks=None,
chief_only_hooks=None,
save_checkpoint_secs=600,
save_summaries_steps=USE_DEFAULT,
save_summaries_secs=USE_DEFAULT,
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. Please check tf.train.MonitoredSession for more information.
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. Default 100.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. Default not enabled.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.A MonitoredSession object.
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/train/MonitoredTrainingSession