xlnstorch.optim.lr_scheduler.LNSPolynomialLR

xlnstorch.optim.lr_scheduler.LNSPolynomialLR#

class xlnstorch.optim.lr_scheduler.LNSPolynomialLR(optimizer, total_iters=5, power=0.9, last_epoch=-1)#

An LNS learning rate scheduler that decays the learning rate of each parameter group by a polynomial factor in the given total_iters.

See also: torch.optim.lr_scheduler.PolynomialLR

Parameters:

  • optimizer (LNSOptimizer) – Wrapped optimizer.

  • total_iters (int) – The number of iterations over which the learning rate will decay.

  • power (float | LNSTensor) – The power of the polynomial decay.

  • last_epoch (int, optional) – The index of last epoch. Default: -1.

__init__(optimizer, total_iters=5, power=0.9, last_epoch=-1)#
Parameters:

  • optimizer (LNSOptimizer)

  • total_iters (int)

  • power (float | LNSTensor)

  • last_epoch (int)

Methods

__init__(optimizer[, total_iters, power, ...])

get_last_lr()

Return last computed learning rate by current scheduler.

get_lr()

Compute the learning rate.

load_state_dict(state_dict)

Load the scheduler's state.

state_dict()

Return the state of the scheduler as a dict.

step([epoch])

Perform a step.
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