| 2 | |
| 3 | |
| 4 | class TrainOptions(BaseOptions): |
| 5 | def initialize(self): |
| 6 | BaseOptions.initialize(self) |
| 7 | self._parser.add_argument('--n_threads_train', default=4, type=int, help='# threads for loading data') |
| 8 | self._parser.add_argument('--num_iters_validate', default=1, type=int, help='# batches to use when validating') |
| 9 | self._parser.add_argument('--print_freq_s', type=int, default=60, help='frequency of showing training results on console') |
| 10 | self._parser.add_argument('--display_freq_s', type=int, default=300, help='frequency [s] of showing training results on screen') |
| 11 | self._parser.add_argument('--save_latest_freq_s', type=int, default=3600, help='frequency of saving the latest results') |
| 12 | |
| 13 | self._parser.add_argument('--nepochs_no_decay', type=int, default=20, help='# of epochs at starting learning rate') |
| 14 | self._parser.add_argument('--nepochs_decay', type=int, default=10, help='# of epochs to linearly decay learning rate to zero') |
| 15 | |
| 16 | self._parser.add_argument('--train_G_every_n_iterations', type=int, default=5, help='train G every n interations') |
| 17 | self._parser.add_argument('--poses_g_sigma', type=float, default=0.06, help='initial learning rate for adam') |
| 18 | self._parser.add_argument('--lr_G', type=float, default=0.0001, help='initial learning rate for G adam') |
| 19 | self._parser.add_argument('--G_adam_b1', type=float, default=0.5, help='beta1 for G adam') |
| 20 | self._parser.add_argument('--G_adam_b2', type=float, default=0.999, help='beta2 for G adam') |
| 21 | self._parser.add_argument('--lr_D', type=float, default=0.0001, help='initial learning rate for D adam') |
| 22 | self._parser.add_argument('--D_adam_b1', type=float, default=0.5, help='beta1 for D adam') |
| 23 | self._parser.add_argument('--D_adam_b2', type=float, default=0.999, help='beta2 for D adam') |
| 24 | self._parser.add_argument('--lambda_D_prob', type=float, default=1, help='lambda for real/fake discriminator loss') |
| 25 | self._parser.add_argument('--lambda_D_cond', type=float, default=4000, help='lambda for condition discriminator loss') |
| 26 | self._parser.add_argument('--lambda_cyc', type=float, default=10, help='lambda cycle loss') |
| 27 | self._parser.add_argument('--lambda_mask', type=float, default=0.1, help='lambda mask loss') |
| 28 | self._parser.add_argument('--lambda_D_gp', type=float, default=10, help='lambda gradient penalty loss') |
| 29 | self._parser.add_argument('--lambda_mask_smooth', type=float, default=1e-5, help='lambda mask smooth loss') |
| 30 | |
| 31 | self.is_train = True |