train.py

import os
from source.trainer import EDGSTrainer
from source.utils_aux import set_seed
import omegaconf
import wandb
import hydra
from argparse import Namespace
from omegaconf import OmegaConf


@hydra.main(config_path="configs", config_name="train", version_base="1.2")
def main(cfg: omegaconf.DictConfig):
    _ = wandb.init(entity=cfg.wandb.entity,
                   project=cfg.wandb.project,
                   config=omegaconf.OmegaConf.to_container(cfg, resolve=True, throw_on_missing=True),
                   tags=[cfg.wandb.tag], 
                   name = cfg.wandb.name,
                   mode = cfg.wandb.mode)
    omegaconf.OmegaConf.resolve(cfg)
    set_seed(cfg.seed)

    # Init output folder
    print("Output folder: {}".format(cfg.gs.dataset.model_path))
    os.makedirs(cfg.gs.dataset.model_path, exist_ok=True)
    with open(os.path.join(cfg.gs.dataset.model_path, "cfg_args"), 'w') as cfg_log_f:
        params = {
                "sh_degree": 3,
                "source_path": cfg.gs.dataset.source_path,
                "model_path": cfg.gs.dataset.model_path,
                "images": cfg.gs.dataset.images,
                "depths": "",
                "resolution": -1,
                "_white_background": cfg.gs.dataset.white_background,
                "train_test_exp": False,
                "data_device": cfg.gs.dataset.data_device,
                "eval": False,
                "convert_SHs_python": False,
                "compute_cov3D_python": False,
                "debug": False,
                "antialiasing": False   
                    }
        cfg_log_f.write(str(Namespace(**params)))

    # Init both agents
    gs = hydra.utils.instantiate(cfg.gs) 

    # Init trainer and launch training
    trainer = EDGSTrainer(GS=gs,
        training_config=cfg.gs.opt,
        device=cfg.device)
    
    trainer.load_checkpoints(cfg.load)
    trainer.timer.start()
    trainer.init_with_corr(cfg.init_wC)      
    trainer.train(cfg.train)
    
    # All done
    wandb.finish()
    print("\nTraining complete.")

if __name__ == "__main__":
    main()