| from .base_options import BaseOptions | |
| class TrainOptions(BaseOptions): | |
| def initialize(self, parser): | |
| parser = BaseOptions.initialize(self, parser) | |
| parser.add_argument('--earlystop_epoch', type=int, default=5) | |
| parser.add_argument('--data_aug', action='store_true', help='if specified, perform additional data augmentation (photometric, blurring, jpegging)') | |
| parser.add_argument('--optim', type=str, default='adam', help='optim to use [sgd, adam]') | |
| parser.add_argument('--new_optim', action='store_true', help='new optimizer instead of loading the optim state') | |
| parser.add_argument('--loss_freq', type=int, default=400, help='frequency of showing loss on tensorboard') | |
| parser.add_argument('--save_latest_freq', type=int, default=2000, help='frequency of saving the latest results') | |
| parser.add_argument('--save_epoch_freq', type=int, default=20, help='frequency of saving checkpoints at the end of epochs') | |
| parser.add_argument('--continue_train', action='store_true', help='continue training: load the latest model') | |
| parser.add_argument('--epoch_count', type=int, default=1, help='the starting epoch count, we save the model by <epoch_count>, <epoch_count>+<save_latest_freq>, ...') | |
| parser.add_argument('--last_epoch', type=int, default=-1, help='starting epoch count for scheduler intialization') | |
| parser.add_argument('--train_split', type=str, default='train', help='train, val, test, etc') | |
| parser.add_argument('--val_split', type=str, default='val', help='train, val, test, etc') | |
| parser.add_argument('--niter', type=int, default=10000, help='# of iter at starting learning rate') | |
| parser.add_argument('--beta1', type=float, default=0.9, help='momentum term of adam') | |
| parser.add_argument('--lr', type=float, default=0.0001, help='initial learning rate for adam') | |
| self.isTrain = True | |
| return parser | |