tf.compat.v1.train.MonitoredTrainingSession

Creates a MonitoredSession for training.

tf.compat.v1.train.MonitoredTrainingSession(
    master='',
    is_chief=True,
    checkpoint_dir=None,
    scaffold=None,
    hooks=None,
    chief_only_hooks=None,
    save_checkpoint_secs=USE_DEFAULT,
    save_summaries_steps=USE_DEFAULT,
    save_summaries_secs=USE_DEFAULT,
    config=None,
    stop_grace_period_secs=120,
    log_step_count_steps=100,
    max_wait_secs=7200,
    save_checkpoint_steps=USE_DEFAULT,
    summary_dir=None,
    save_graph_def=True
)

Migrate to TF2

This API is not compatible with eager execution and tf.function. To migrate to TF2, rewrite the code to be compatible with eager execution. Check the migration guide on replacing Session.run calls. In Keras, session hooks can be replaced by Callbacks e.g. logging hook notebook For more details please read Better performance with tf.function.

Description

Used in the notebooks

Used in the tutorials

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.compat.v1.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 both save_checkpoint_steps and save_checkpoint_secs are set to None, then the default checkpoint saver isn't used. If both are provided, then only save_checkpoint_secs is used. Default 600.
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.compat.v1.ConfigProto proto used to configure the session. It's the config argument of constructor of tf.compat.v1.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.
max_wait_secs Maximum time workers should wait for the session to become available. This should be kept relatively short to help detect incorrect code, but sometimes may need to be increased if the chief takes a while to start up.
save_checkpoint_steps The frequency, in number of global steps, that a checkpoint is saved using a default checkpoint saver. If both save_checkpoint_steps and save_checkpoint_secs are set to None, then the default checkpoint saver isn't used. If both are provided, then only save_checkpoint_secs is used. Default not enabled.
summary_dir A string. Optional path to a directory where to save summaries. If None, checkpoint_dir is used instead.
save_graph_def Whether to save the GraphDef and MetaGraphDef to checkpoint_dir. The GraphDef is saved after the session is created as graph.pbtxt. MetaGraphDefs are saved out for every checkpoint as model.ckpt-*.meta.

A MonitoredSession object.