tf.contrib.learn.monitors.EveryN.run_on_all_workers

tf.contrib.learn.monitors.EveryN.run_on_all_workers

tf.contrib.learn.monitors.EveryN.post_step()

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

tf.contrib.learn.monitors.EveryN.every_n_step_end()

tf.contrib.learn.monitors.EveryN.every_n_step_end(step, outputs) Callback after every n'th step finished. This callback provides access to the tensors/ops evaluated at this step, including the additional tensors for which evaluation was requested in step_begin. In addition, the callback has the opportunity to stop training by returning True. This is useful for early stopping, for example. Args: step: int, the current value of the global step. outputs: dict mapping string values representing

tf.contrib.learn.monitors.EveryN.every_n_step_begin()

tf.contrib.learn.monitors.EveryN.every_n_step_begin(step) Callback before every n'th step begins. Args: step: int, the current value of the global step. Returns: A list of tensors that will be evaluated at this step.

tf.contrib.learn.monitors.EveryN.every_n_post_step()

tf.contrib.learn.monitors.EveryN.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.EveryN.epoch_end()

tf.contrib.learn.monitors.EveryN.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.EveryN.epoch_begin()

tf.contrib.learn.monitors.EveryN.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.EveryN.end()

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

tf.contrib.learn.monitors.EveryN.begin()

tf.contrib.learn.monitors.EveryN.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.

tf.contrib.learn.monitors.EveryN

class tf.contrib.learn.monitors.EveryN Base class for monitors that execute callbacks every N steps. This class adds three new callbacks: - every_n_step_begin - every_n_step_end - every_n_post_step The callbacks are executed every n steps, or optionally every step for the first m steps, where m and n can both be user-specified. When extending this class, note that if you wish to use any of the BaseMonitor callbacks, you must call their respective super implementation: def step_begin(self, step