def __init__(self,
lr=1e-4,
beta_1=0.9,
beta_2=0.999,
epsilon=1e-8,
save=False,
rng=None,
*args,
**kwargs):
print('args=%s' % str(args))
print('kwargs=%s' % str(kwargs))
super(Adam, self).__init__(**kwargs)
self.__dict__.update(locals())
print(locals())
# if 'iterations' in kwargs:
# print('iterations=%s' % str(kwargs['iterations']))
# self.iterations = shared_scalar(kwargs['iterations'], name='iteration')
# else:
# print('iterations not set')
# self.iterations = shared_scalar(0, name='iteration')
self.iterations = shared_scalar(0, name='iteration')
self.lr = shared_scalar(lr, name='lr')
# self.rng = MRG_RandomStreams(use_cuda=True)
self.noise = []
self.forget = dict()
# self.rng = rng
self.beta_1 = beta_1
self.beta_2 = beta_2
self.epsilon = epsilon
self.add(self.iterations)
self.add(self.lr)
def __init__(self,
lr=0.05,
momentum=0.9,
decay=0.01,
nesterov=True,
*args,
**kwargs):
super(SGD, self).__init__(**kwargs)
self.__dict__.update(locals())
self.iterations = shared_scalar(0)
self.lr = shared_scalar(lr)
self.momentum = shared_scalar(momentum)
def __init__(self,
lr=0.001,
beta_1=0.9,
beta_2=0.999,
epsilon=1e-8,
save=False,
rng=None,
*args,
**kwargs):
super(Adam, self).__init__(**kwargs)
self.__dict__.update(locals())
print(locals())
self.iterations = shared_scalar(0, name='iteration')
self.lr = shared_scalar(lr, name='lr')
self.rng = MRG_RandomStreams(use_cuda=True)
self.noise = []
self.forget = dict()
self.rng = rng
self.add(self.iterations)
self.add(self.lr)
def __init__(self, lr=0.1, rho=0.95, epsilon=1e-6, *args, **kwargs):
super(Adadelta, self).__init__(**kwargs)
self.__dict__.update(locals())
self.lr = shared_scalar(lr)
self.iterations = shared_scalar(0)
def __init__(self, lr=0.01, epsilon=1e-6, *args, **kwargs):
super(Adagrad, self).__init__(**kwargs)
self.__dict__.update(locals())
self.lr = shared_scalar(lr)
def __init__(self, lr=0.001, rho=0.9, epsilon=1e-6, *args, **kwargs):
super(RMSprop, self).__init__(**kwargs)
self.__dict__.update(locals())
self.lr = shared_scalar(lr)
self.rho = shared_scalar(rho)
self.iterations = shared_scalar(0)