Update generated Python Op docs.
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### `tf.train.MonitoredTrainingSession(master='', is_chief=True, checkpoint_dir=None, scaffold=None, hooks=None, chief_only_hooks=None, save_checkpoint_secs=600, save_summaries_steps=100, config=None)` {#MonitoredTrainingSession}
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### `tf.train.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)` {#MonitoredTrainingSession}
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Creates a `MonitoredSession` for training.
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@ -26,8 +26,12 @@ inialize/restore.
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using a default checkpoint saver. If `save_checkpoint_secs` is set to
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`None`, then the default checkpoint saver isn't used.
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* <b>`save_summaries_steps`</b>: The frequency, in number of global steps, that the
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summaries are written to disk using a default summary saver. If
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`save_summaries_steps` is set to `None`, then the default summary saver
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summaries are written to disk using a default summary saver. If both
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`save_summaries_steps` and `save_summaries_secs` are set to `None`, then
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the default summary saver isn't used.
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* <b>`save_summaries_secs`</b>: The frequency, in secs, that the summaries are written
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to disk using a default summary saver. If both `save_summaries_steps` and
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`save_summaries_secs` are set to `None`, then the default summary saver
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isn't used.
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* <b>`config`</b>: an instance of `tf.ConfigProto` proto used to configure the session.
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It's the `config` argument of constructor of `tf.Session`.
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@ -3531,7 +3531,7 @@ with tf.device(tf.train.replica_device_setter(cluster=cluster_spec)):
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- - -
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### `tf.train.MonitoredTrainingSession(master='', is_chief=True, checkpoint_dir=None, scaffold=None, hooks=None, chief_only_hooks=None, save_checkpoint_secs=600, save_summaries_steps=100, config=None)` {#MonitoredTrainingSession}
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### `tf.train.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)` {#MonitoredTrainingSession}
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Creates a `MonitoredSession` for training.
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@ -3559,8 +3559,12 @@ inialize/restore.
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using a default checkpoint saver. If `save_checkpoint_secs` is set to
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`None`, then the default checkpoint saver isn't used.
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* <b>`save_summaries_steps`</b>: The frequency, in number of global steps, that the
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summaries are written to disk using a default summary saver. If
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`save_summaries_steps` is set to `None`, then the default summary saver
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summaries are written to disk using a default summary saver. If both
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`save_summaries_steps` and `save_summaries_secs` are set to `None`, then
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the default summary saver isn't used.
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* <b>`save_summaries_secs`</b>: The frequency, in secs, that the summaries are written
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to disk using a default summary saver. If both `save_summaries_steps` and
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`save_summaries_secs` are set to `None`, then the default summary saver
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isn't used.
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* <b>`config`</b>: an instance of `tf.ConfigProto` proto used to configure the session.
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It's the `config` argument of constructor of `tf.Session`.
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