paddlespeech.vector.training.scheduler module

class paddlespeech.vector.training.scheduler.CyclicLRScheduler(base_lr: float = 1e-08, max_lr: float = 0.001, step_size: int = 10000)

Bases: LRScheduler

Methods

__call__()	Return lastest computed learning rate on current epoch.
get_lr()	For those subclass who overload LRScheduler (Base Class), User should have a custom implementation of get_lr() .
set_dict(state_dict)	Loads the schedulers state.
set_state_dict(state_dict)	Loads the schedulers state.
state_dict()	Returns the state of the scheduler as a dict.
state_keys()	For those subclass who overload LRScheduler (Base Class).
step()	step should be called after optimizer.step .

get_lr()

For those subclass who overload LRScheduler (Base Class), User should have a custom implementation of get_lr() .

Otherwise, an NotImplementedError exception will be thrown.

step()

step should be called after optimizer.step . It will update the learning rate in optimizer according to current epoch . The new learning rate will take effect on next optimizer.step .

Args:

epoch (int, None): specify current epoch. Default: None. Auto-increment from last_epoch=-1.

Returns:

None