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())