ashpy.callbacks¶

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.

Order:

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

Classes

`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.

Modules

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