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