Additional callbacks which make decisions depending how a monitored metric/loss behaves.

class TerminateOnTrainNaN[source]

TerminateOnTrainNaN(after_create=None, before_fit=None, before_epoch=None, before_train=None, before_batch=None, after_pred=None, after_loss=None, before_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) :: Callback

A Callback that terminates training if the training loss is NaN and ignores valid loss.

class SaveModelAtEnd[source]

SaveModelAtEnd(fname='model', with_opt=False) :: SaveModelCallback

A SaveModelCallback which only saves the model at the end so loggers can find it.

Type Default Details
fname str model Model filename
with_opt bool False Include optimizer state