def _default_opt(self):
self.opt = opt.opt()
self.opt.save_dir = 'checkpoints'
self.opt.name = 'Facelet'
self.opt.lr = 1e-4
self.opt.pretrained = True
self.opt.effect = 'facehair'
def __init__(self, opt=opt.opt()):
super(Facelet, self).__init__()
self._default_opt()
self.opt = self.opt.merge_opt(opt)
self._define_model()
self._define_optimizer()
if self.opt.pretrained:
state_dict = util.load_from_url(model_urls[self.opt.effect], save_dir=facelet_path)
model_dict = self.model.state_dict()
model_dict.update(state_dict)
self.model.load_state_dict(model_dict)
def __init__(self, model, option=opt.opt()):
super(optimizer, self).__init__()
self._default_opt()
self.opt.merge_opt(option)
self._get_model(model)
self._get_aux_nets()
self._define_optim()
# self.writer = curves.writer(log_dir=self.opt.save_dir + '/log')
util.mkdir(self.opt.save_dir + '/log')
self.writer = tensorboardX.SummaryWriter(log_dir=self.opt.save_dir +
'/log')
if self.opt.continue_train:
self.load()
def _default_opt(self):
self.opt = opt.opt()
self.opt.save_dir = '/checkpoints/default'
self.opt.n_discrim = 5
def _default_opt(self):
self.opt = opt.opt()
self.opt.continue_train = False
self.opt.lr = 1e-3