| 449 | } |
| 450 | |
| 451 | void NeuralScene::UpdateLearningRate(int epoch_id, double factor) |
| 452 | { |
| 453 | SAIGA_ASSERT(factor > 0); |
| 454 | |
| 455 | double lr_update_adam = factor; |
| 456 | |
| 457 | double lr_update_sgd = factor; |
| 458 | |
| 459 | if (texture_optimizer) |
| 460 | { |
| 461 | if (params->optimizer_params.texture_optimizer == "adam") |
| 462 | { |
| 463 | UpdateLR(texture_optimizer.get(), lr_update_adam); |
| 464 | } |
| 465 | else if (params->optimizer_params.texture_optimizer == "sgd") |
| 466 | { |
| 467 | UpdateLR(texture_optimizer.get(), lr_update_sgd); |
| 468 | } |
| 469 | else |
| 470 | { |
| 471 | SAIGA_EXIT_ERROR("sldg"); |
| 472 | } |
| 473 | } |
| 474 | |
| 475 | if (epoch_id > params->train_params.lock_camera_params_epochs) |
| 476 | { |
| 477 | if (camera_adam_optimizer) |
| 478 | { |
| 479 | UpdateLR(camera_adam_optimizer.get(), lr_update_adam); |
| 480 | } |
| 481 | if (camera_sgd_optimizer) |
| 482 | { |
| 483 | UpdateLR(camera_sgd_optimizer.get(), lr_update_sgd); |
| 484 | } |
| 485 | } |
| 486 | |
| 487 | if (structure_optimizer && epoch_id > params->train_params.lock_structure_params_epochs) |
| 488 | { |
| 489 | UpdateLR(structure_optimizer.get(), lr_update_sgd); |
| 490 | } |
| 491 | } |
| 492 | |
| 493 | void NeuralScene::DownloadIntrinsics() |
| 494 | { |