本文整理汇总了Python中models.resnet.get_fine_tuning_parameters方法的典型用法代码示例。如果您正苦于以下问题:Python resnet.get_fine_tuning_parameters方法的具体用法?Python resnet.get_fine_tuning_parameters怎么用?Python resnet.get_fine_tuning_parameters使用的例子?那么, 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models.resnet
的用法示例。
在下文中一共展示了resnet.get_fine_tuning_parameters方法的1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: get_model_param
# 需要导入模块: from models import resnet [as 别名]
# 或者: from models.resnet import get_fine_tuning_parameters [as 别名]
def get_model_param(args):
# assert args.model in ['resnet', 'vgg']
if args.model == 'resnet':
assert args.model_depth in [18, 34, 50, 101, 152]
from models.resnet import get_fine_tuning_parameters
if args.model_depth == 18:
model = resnet.resnet18(pretrained=False, input_size=args.input_size, num_classes=args.n_classes)
elif args.model_depth == 34:
model = resnet.resnet34(pretrained=False, input_size=args.input_size, num_classes=args.n_classes)
elif args.model_depth == 50:
model = resnet.resnet50(pretrained=False, input_size=args.input_size, num_classes=args.n_classes)
elif args.model_depth == 101:
model = resnet.resnet101(pretrained=False, input_size=args.input_size, num_classes=args.n_classes)
elif args.model_depth == 152:
model = resnet.resnet152(pretrained=False, input_size=args.input_size, num_classes=args.n_classes)
# elif args.model == 'vgg':
# pass
# Load pretrained model here
if args.finetune:
pretrained_model = model_path[args.arch]
args.pretrain_path = os.path.join(args.root_path, 'pretrained_models', pretrained_model)
print("=> loading pretrained model '{}'...".format(pretrained_model))
model.load_state_dict(torch.load(args.pretrain_path))
# Only modify the last layer
if args.model == 'resnet':
model.fc = nn.Linear(model.fc.in_features, args.n_finetune_classes)
# elif args.model == 'vgg':
# pass
parameters = get_fine_tuning_parameters(model, args.ft_begin_index, args.lr_mult1, args.lr_mult2)
return model, parameters
return model, model.parameters()