DataAug

class radionets.core.callbacks.DataAug(*, after_create=None, before_fit=None, before_epoch=None, before_train=None, before_batch=None, after_pred=None, after_loss=None, before_backward=None, after_cancel_backward=None, after_backward=None, before_step=None, after_cancel_step=None, after_step=None, after_cancel_batch=None, after_batch=None, after_cancel_train=None, after_train=None, before_validate=None, after_cancel_validate=None, after_validate=None, after_cancel_epoch=None, after_epoch=None, after_cancel_fit=None, after_fit=None)

Bases: Callback

Callback that applies data augmentation using random rotations.

Applies random multiples of 90-degree rotations to both input and target tensors before each batch to augment the training data.

Attributes Summary

learn
name	Name of the Callback, camel-cased and with 'Callback' removed
order
run
run_train
run_valid

Methods Summary

__call__(event_name)	Call self.{event_name} if it's defined
before_batch()

Attributes Documentation

learn = None

name

Name of the Callback, camel-cased and with ‘Callback’ removed

order = 0

run = True

run_train = True

run_valid = True

Methods Documentation

__call__(event_name)

Call self.{event_name} if it’s defined

before_batch()