A wrapper around
contrib.training.train that uses GAN hooks.
tf.contrib.gan.gan_train( train_ops, logdir, get_hooks_fn=get_sequential_train_hooks(), master='', is_chief=True, scaffold=None, hooks=None, chief_only_hooks=None, save_checkpoint_secs=600, save_summaries_steps=100, config=None )
train_ops: A GANTrainOps named tuple.
logdir: The directory where the graph and checkpoints are saved.
get_hooks_fn: A function that takes a GANTrainOps tuple and returns a list of hooks.
master: The URL of the master.
is_chief: Specifies whether or not the training is being run by the primary replica during replica training.
scaffold: An tf.compat.v1.train.Scaffold instance.
hooks: List of
tf.estimator.SessionRunHookcallbacks which are run inside the training loop.
chief_only_hooks: List of
tf.estimator.SessionRunHookinstances which are run inside the training loop for the chief trainer only.
save_checkpoint_secs: The frequency, in seconds, that a checkpoint is saved using a default checkpoint saver. If
save_checkpoint_secsis 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
save_summaries_stepsis set to
None, then the default summary saver isn't used.
config: An instance of
Output of the call to