tf.contrib.learn.monitors.ExportMonitor.every_n_post_step(step, session) Callback after a step is finished or end() is called. Args: step: int, the current value of the global step. session: Session object.

tf.contrib.learn.monitors.ExportMonitor.epoch_end(epoch) End epoch. Args: epoch: int, the epoch number. Raises: ValueError: if we've not begun an epoch, or epoch number does not match.

tf.contrib.learn.monitors.ExportMonitor.epoch_begin(epoch) Begin epoch. Args: epoch: int, the epoch number. Raises: ValueError: if we've already begun an epoch, or epoch < 0.

tf.contrib.learn.monitors.ExportMonitor.end(session=None)

tf.contrib.learn.monitors.ExportMonitor.begin(max_steps=None) Called at the beginning of training. When called, the default graph is the one we are executing. Args: max_steps: int, the maximum global step this training will run until. Raises: ValueError: if we've already begun a run.

class tf.contrib.learn.monitors.ExportMonitor Monitor that exports Estimator every N steps.

tf.contrib.learn.monitors.EveryN.__init__(every_n_steps=100, first_n_steps=1) Initializes an EveryN monitor. Args: every_n_steps: int, the number of steps to allow between callbacks. first_n_steps: int, specifying the number of initial steps during which the callbacks will always be executed, regardless of the value of every_n_steps. Note that this value is relative to the global step

tf.contrib.learn.monitors.EveryN.step_end(step, output) Overrides BaseMonitor.step_end. When overriding this method, you must call the super implementation. Args: step: int, the current value of the global step. output: dict mapping string values representing tensor names to the value resulted from running these tensors. Values may be either scalars, for scalar tensors, or Numpy array, for non-scalar tensors. Returns: bool, the result of every_n_step_end, if that was called this step, or F

tf.contrib.learn.monitors.EveryN.step_begin(step) Overrides BaseMonitor.step_begin. When overriding this method, you must call the super implementation. Args: step: int, the current value of the global step. Returns: A list, the result of every_n_step_begin, if that was called this step, or an empty list otherwise. Raises: ValueError: if called more than once during a step.

tf.contrib.learn.monitors.EveryN.set_estimator(estimator) A setter called automatically by the target estimator. If the estimator is locked, this method does nothing. Args: estimator: the estimator that this monitor monitors. Raises: ValueError: if the estimator is None.