本文整理汇总了Python中utility.make_optimizer方法的典型用法代码示例。如果您正苦于以下问题：Python utility.make_optimizer方法的具体用法？Python utility.make_optimizer怎么用？Python utility.make_optimizer使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类utility的用法示例。
在下文中一共展示了utility.make_optimizer方法的6个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
# 需要导入模块: import utility [as 别名]
# 或者: from utility import make_optimizer [as 别名]
def __init__(self, args, loader, my_model, my_loss, ckp):
self.args = args
self.scale = args.scale
self.ckp = ckp
self.loader_train = loader.loader_train
self.loader_test = loader.loader_test
self.model = my_model
self.loss = my_loss
self.optimizer = utility.make_optimizer(args, self.model)
self.scheduler = utility.make_scheduler(args, self.optimizer)
if self.args.load != '':
self.optimizer.load_state_dict(
torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
)
for _ in range(len(ckp.log)): self.scheduler.step()
self.error_last = 1e8 示例2: __init__
# 需要导入模块: import utility [as 别名]
# 或者: from utility import make_optimizer [as 别名]
def __init__(self, args, gan_type):
super(Adversarial, self).__init__()
self.gan_type = gan_type
self.gan_k = args.gan_k
self.dis = discriminator.Discriminator(args)
if gan_type == 'WGAN_GP':
# see https://arxiv.org/pdf/1704.00028.pdf pp.4
optim_dict = {
'optimizer': 'ADAM',
'betas': (0, 0.9),
'epsilon': 1e-8,
'lr': 1e-5,
'weight_decay': args.weight_decay,
'decay': args.decay,
'gamma': args.gamma
}
optim_args = SimpleNamespace(**optim_dict)
else:
optim_args = args
self.optimizer = utility.make_optimizer(optim_args, self.dis) 示例3: __init__
# 需要导入模块: import utility [as 别名]
# 或者: from utility import make_optimizer [as 别名]
def __init__(self, args, loader, my_model, my_loss, ckp):
self.args = args
self.scale = args.scale
self.ckp = ckp
self.loader_train = loader.loader_train
self.loader_test = loader.loader_test
self.model = my_model
self.loss = my_loss
self.optimizer = utility.make_optimizer(args, self.model)
self.scheduler = utility.make_scheduler(args, self.optimizer)
if self.args.load != '.':
self.optimizer.load_state_dict(
torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
)
for _ in range(len(ckp.log)): self.scheduler.step()
self.error_last = 1e8 示例4: __init__
# 需要导入模块: import utility [as 别名]
# 或者: from utility import make_optimizer [as 别名]
def __init__(self, args, loader, my_model, my_loss, ckp):
self.args = args
self.scale = args.scale
self.ckp = ckp
self.loader_train = loader.loader_train
self.loader_test = loader.loader_test
self.model = my_model
self.loss = my_loss
self.optimizer = utility.make_optimizer(args, self.model)
self.scheduler = utility.make_scheduler(args, self.optimizer)
if self.args.load != '.':
self.optimizer.load_state_dict(
torch.load(os.path.join(ckp.dir, 'optimizer.pt'))
)
for _ in range(len(ckp.log)): self.scheduler.step()
self.error_last = 1e8
del args,ckp,my_model,my_loss 示例5: __init__
# 需要导入模块: import utility [as 别名]
# 或者: from utility import make_optimizer [as 别名]
def __init__(self, args, gan_type):
super(Adversarial, self).__init__()
self.gan_type = gan_type
self.gan_k = args.gan_k
self.discriminator = discriminator.Discriminator(args, gan_type)
if gan_type != 'WGAN_GP':
self.optimizer = utility.make_optimizer(args, self.discriminator)
else:
self.optimizer = optim.Adam(
self.discriminator.parameters(),
betas=(0, 0.9), eps=1e-8, lr=1e-5
)
self.scheduler = utility.make_scheduler(args, self.optimizer) 示例6: __init__
# 需要导入模块: import utility [as 别名]
# 或者: from utility import make_optimizer [as 别名]
def __init__(self, args, loader, my_model, my_loss, ckp):
self.args = args
self.scale = args.scale
self.ckp = ckp
self.loader_train = loader.loader_train
self.loader_test = loader.loader_test
self.model = my_model
self.loss = my_loss
self.optimizer = utility.make_optimizer(args, self.model)
if self.args.load != '':
self.optimizer.load(ckp.dir, epoch=len(ckp.log))
self.error_last = 1e8