LRScheduler

class LRScheduler(optimizer: Optimizer, last_epoch=-1, verbose='deprecated')

Bases: object

Adjusts the learning rate during optimization.

Methods Summary

get_last_lr()	Return last computed learning rate by current scheduler.
get_lr()	Compute learning rate using chainable form of the scheduler.
load_state_dict(state_dict)	Load the scheduler's state.
print_lr(is_verbose, group, lr[, epoch])	Display the current learning rate.
state_dict()	Return the state of the scheduler as a dict.
step([epoch])	Perform a step.

Methods Documentation

Parameters:

optimizer (Optimizer)

get_last_lr() → List[float]

Return last computed learning rate by current scheduler.

Return type:

List[float]

get_lr() → List[float]

Compute learning rate using chainable form of the scheduler.

Return type:

List[float]

load_state_dict(state_dict: Dict[str, Any])

Load the scheduler’s state.

Args:

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

from a call to state_dict().

Parameters:

state_dict (Dict[str, Any])

print_lr(is_verbose: bool, group: Dict[str, Any], lr: float, epoch: int | None = None)

Display the current learning rate.

Deprecated since version 2.4: print_lr() is deprecated. Please use get_last_lr() to access the learning rate.

Parameters:

• is_verbose (bool)

• group (Dict[str, Any])

• lr (float)

• epoch (int | None)

state_dict()

Return the state of the scheduler as a dict.

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

step(epoch: int | None = None)

Perform a step.

Parameters:

epoch (int | None)