dlpy.lr_scheduler.PolynomialLR

class dlpy.lr_scheduler.PolynomialLR(learning_rate, power)

Bases: dlpy.lr_scheduler._LRScheduler

Polynomial learning rate scheduler Applies a polynomial decay to the learning rate calculated by: lr = initial_lr * (1 −iter / maxiter ) ^ power

Parameters:

learning_rate : double, optional

Specifies the initial learning rate.

power : double, optional

Specifies the power for the learning rate policy.

Returns:

PolynomialLR

__init__(learning_rate, power)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(learning_rate, power)	Initialize self.
clear()
get(k[,d])
items()
keys()
pop(k[,d])	If key is not found, d is returned if given, otherwise KeyError is raised.
popitem()	as a 2-tuple; but raise KeyError if D is empty.
setdefault(k[,d])
update([E, ]**F)	If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
values()