deepof.model_utils.CustomStopper

class deepof.model_utils.CustomStopper(start_epoch, *args, **kwargs)

Custom early stopping callback. Prevents the model from stopping before warmup is over.

__init__(start_epoch, *args, **kwargs)

Initialize the CustomStopper callback.

Parameters:

  • start_epoch – epoch from which performance will be taken into account when deciding whether to stop training.

  • *args – arguments passed to the callback.

  • **kwargs – keyword arguments passed to the callback.

Methods

__init__(start_epoch, *args, **kwargs)

Initialize the CustomStopper callback.

get_config()

Update callback metadata.

get_monitor_value(logs)

on_batch_begin(batch[, logs])

A backwards compatibility alias for on_train_batch_begin.

on_batch_end(batch[, logs])

A backwards compatibility alias for on_train_batch_end.

on_epoch_begin(epoch[, logs])

Called at the start of an epoch.

on_epoch_end(epoch[, logs])

Check whether to stop training.

on_predict_batch_begin(batch[, logs])

Called at the beginning of a batch in predict methods.

on_predict_batch_end(batch[, logs])

Called at the end of a batch in predict methods.

on_predict_begin([logs])

Called at the beginning of prediction.

on_predict_end([logs])

Called at the end of prediction.

on_test_batch_begin(batch[, logs])

Called at the beginning of a batch in evaluate methods.

on_test_batch_end(batch[, logs])

Called at the end of a batch in evaluate methods.

on_test_begin([logs])

Called at the beginning of evaluation or validation.

on_test_end([logs])

Called at the end of evaluation or validation.

on_train_batch_begin(batch[, logs])

Called at the beginning of a training batch in fit methods.

on_train_batch_end(batch[, logs])

Called at the end of a training batch in fit methods.

on_train_begin([logs])

Called at the beginning of training.

on_train_end([logs])

Called at the end of training.

set_model(model)

set_params(params)

__init__(start_epoch, *args, **kwargs)

Initialize the CustomStopper callback.

Parameters:

  • start_epoch – epoch from which performance will be taken into account when deciding whether to stop training.

  • *args – arguments passed to the callback.

  • **kwargs – keyword arguments passed to the callback.