deepof.model_utils.ExponentialLearningRate
- class deepof.model_utils.ExponentialLearningRate(factor: float)
Simple class that allows to grow learning rate exponentially during training.
Used to trigger optimal learning rate search in deepof.train_utils.find_learning_rate.
- __init__(factor: float)
Initialize the exponential learning rate callback.
- Parameters:
factor (float) – factor by which to multiply the learning rate
Methods
__init__
(factor)Initialize the exponential learning rate callback.
on_batch_begin
(batch[, logs])A backwards compatibility alias for on_train_batch_begin.
on_batch_end
(batch, logs)Apply on batch end.
on_epoch_begin
(epoch[, logs])Called at the start of an epoch.
on_epoch_end
(epoch[, logs])Called at the end of an epoch.
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__(factor: float)
Initialize the exponential learning rate callback.
- Parameters:
factor (float) – factor by which to multiply the learning rate