Exponential

class olympus.optimizers.schedules.exponential.ExponentialLR(optimizer, gamma)

Bases: olympus.optimizers.schedules.base.LRScheduleAdapter

Methods

get_last_lr(self)	Return last computed learning rate by current scheduler.
load_state_dict(self, state_dict)	Loads the schedulers state.
state_dict(self)	Returns the state of the scheduler as a dict.

defaults
epoch
get_lr
get_space
step

static defaults()

epoch(self, epoch=None, metrics=None)

static get_space()

load_state_dict(self, state_dict)

Loads the schedulers state.

Arguments:

state_dict (dict): scheduler state. Should be an object returned

from a call to state_dict().

state_dict(self)

Returns the state of the scheduler as a dict.

It contains an entry for every variable in self.__dict__ which is not the optimizer.

step(self, step=None, metrics=None)