dlpy.lr_scheduler.FCMPLR

class dlpy.lr_scheduler.FCMPLR(conn, fcmp_learning_rate, learning_rate=0.001, gamma=0.1, step_size=10)

Bases: dlpy.lr_scheduler._LRScheduler

FCMP learning rate scheduler. Customize you own defined learning rate policy. For more details, please check one example at: examples/learning_rate_policy/Define_Learning_Rate_Policy.ipynb.

Parameters:

conn : CAS

Specifies the CAS connection object.

fcmp_learning_rate : string

specifies the FCMP learning rate function.

learning_rate : double, optional

Specifies the initial learning rate.

gamma : double, optional

Specifies the gamma for the learning rate policy.

step_size : int, optional

Specifies the step size when the learning rate policy is set to STEP.

Returns:

FCMPLR

__init__(conn, fcmp_learning_rate, learning_rate=0.001, gamma=0.1, step_size=10)

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

Methods

__init__(conn, fcmp_learning_rate[, …])	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()