Listeners

Listeners allow you to customise the behaviour of the training loop at specific points, such as the start of an epoch or after a batch.

Built-in Listeners

REAX comes with several built-in listeners:

• ModelCheckpoint: Automatically save model checkpoints based on a monitored metric.

• EarlyStopping: Stop training early if a metric stops improving.

• ProgressBar: Display a progress bar during training.

Custom Listeners

You can create your own listener by inheriting from TrainerListener.

import reax

class MyPrintingListener(reax.TrainerListener):
    def on_train_start(self, trainer, module):
        print("Training is starting!")

    def on_train_end(self, trainer, module):
        print("Training is ending!")

Using Listeners

Pass your listeners to the Trainer:

trainer = reax.Trainer(listeners=[MyPrintingListener()])

Order of Execution

Listeners are executed in the order they are passed to the Trainer.