dlpy.lr_scheduler.PolynomialLR¶
-
class
dlpy.lr_scheduler.PolynomialLR(learning_rate, power)¶ Polynomial learning rate scheduler Applies a polynomial decay to the learning rate calculated by: lr = initial_lr * (1 −iter / maxiter ) ^ power
- Parameters
- learning_ratedouble, optional
Specifies the initial learning rate.
- powerdouble, optional
Specifies the power for the learning rate policy.
- Returns
-
__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()