tf.contrib.learn.monitors.PrintTensor.epoch_begin(epoch) Begin epoch. Args:

tf.contrib.learn.monitors.CheckpointSaver.run_on_all_workers

tf.contrib.learn.monitors.LoggingTrainable.__init__(scope=None, every_n=100, first_n=1) Initializes LoggingTrainable monitor.

tf.contrib.learn.monitors.RunHookAdapterForMonitors.after_run(run_context, run_values)

tf.contrib.learn.monitors.CaptureVariable.epoch_begin(epoch) Begin epoch. Args:

tf.contrib.learn.monitors.EveryN.post_step(step, session)

class tf.contrib.learn.monitors.NanLoss NaN Loss monitor. Monitors loss and stops training if

tf.contrib.learn.monitors.ValidationMonitor.epoch_end(epoch) End epoch. Args:

class tf.contrib.learn.monitors.EveryN Base class for monitors that execute callbacks every N steps. This

tf.contrib.learn.monitors.CaptureVariable.every_n_post_step(step, session) Callback after a step is finished or end()