def __init__(self,
epsilon=1e-8,
lr=None,
weight_decay=None,
lr_gen=None,
regularizer=None,
constraint=None):
super(RMSProp, self).__init__(lr, weight_decay, lr_gen, regularizer,
constraint)
conf = model_pb2.OptimizerConf()
conf.delta = epsilon
conf.type = 'adagrad'
self.opt = singa.CreateOptimizer('AdaGrad')
self.opt.Setup(conf.SerializeToString())
def __init__(self,
rho=0.9,
epsilon=1e-8,
lr=None,
weight_decay=None,
regularizer=None,
constraint=None):
super(RMSProp, self).__init__(lr, None, weight_decay, regularizer,
constraint)
conf = model_pb2.OptimizerConf()
conf.rho = rho
conf.delta = epsilon
self.opt = singa.CreateOptimizer('RMSProp')
self.opt.Setup(conf.SerializeToString())
def __init__(self,
lr=None,
momentum=0.9,
weight_decay=None,
regularizer=None,
constraint=None):
super(Nesterov, self).__init__(lr, momentum, weight_decay, regularizer,
constraint)
conf = model_pb2.OptimizerConf()
if self.momentum is not None:
conf.momentum = momentum
conf.type = 'nesterov'
self.opt = singa.CreateOptimizer('Nesterov')
self.opt.Setup(conf.SerializeToString())
def __init__(self,
lr=None,
momentum=None,
weight_decay=None,
lr_gen=None,
regularizer=None,
constraint=None):
super(SGD, self).__init__(lr, momentum, weight_decay, lr_gen,
regularizer, constraint)
conf = model_pb2.OptimizerConf()
if self.momentum is not None:
conf.momentum = self.momentum
conf.type = 'sgd'
self.opt = singa.CreateOptimizer('SGD')
self.opt.Setup(conf.SerializeToString())
