Callbacks in order to gain control over the training loop.

A callback is a set of functions to be called at given stages of the training procedure. You can use callbacks to implement logging, measure custom metrics or get insight about the training procedure. You can pass a list of callbacks (derived from ashpy.callbacks.callback.Callback) (as the keyword argument callbacks) to the .call() method of the Trainer. The relevant methods of the callbacks will then be called at each stage of the training.


The basic class is ashpy.callbacks.callback.Callback . All possible events as listed as Enum inside .


callback.Callback Callback definition.
counter_callback.CounterCallback Count events of a specific type.
classifier.LogClassifierCallback Callback used for logging Classifier images to Tensorboard.
events.Event Define all possible events.
gan.LogImageGANCallback Callback used for logging GANs images to Tensorboard.
gan.LogImageGANEncoderCallback Callback used for logging GANs images to Tensorboard.
save_callback.SaveCallback Save Callback implementation.
save_callback.SaveFormat Save Format enum.
save_callback.SaveSubFormat Save Sub-Format enum.


callback Callback definition.
classifier Classifier callbacks.
counter_callback Counter Callback implementation.
events Event definition as Enum.
gan GAN callbacks.
save_callback Save weights callback.