| import os |
| import sys |
| from pathlib import Path |
| import logging |
| project_dir = Path(__file__).absolute().parent.parent |
| sys.path.append(str(project_dir)) |
|
|
| import hydra |
| from hydra.core.hydra_config import HydraConfig |
| from omegaconf import DictConfig, OmegaConf |
| OmegaConf.register_new_resolver("eval", eval) |
|
|
| import torch |
| import torch.distributed as dist |
| from ml_collections.config_dict import ConfigDict |
|
|
| from src.utils.inference.dumper import DataDumper |
| from src.utils.inference.infer_runner import InferRunner |
| from src.data.dataloader import get_inference_dataloader |
| from src.model.odesign import ODesign |
| from src.utils.train.distributed import DIST_WRAPPER |
| from src.utils.misc import print_configs |
|
|
| logger = logging.getLogger(__name__) |
|
|
|
|
| @hydra.main( |
| version_base="1.3", config_path=str(project_dir/"configs"), config_name="inference" |
| ) |
| def main(configs : DictConfig) -> None: |
| |
| print_configs(configs) |
| os.environ["DATA_ROOT_DIR"] = configs.data_root_dir |
| os.environ["CKPT_ROOT_DIR"] = configs.ckpt_root_dir |
| configs = ConfigDict( |
| OmegaConf.to_container(configs.exp, resolve=True) |
| ) |
| dump_dir = HydraConfig.get().runtime.output_dir |
| configs.dump_dir = dump_dir |
| error_dir = Path(dump_dir) / "errors" |
| if DIST_WRAPPER.rank == 0: |
| error_dir.mkdir(parents=True, exist_ok=True) |
|
|
| |
| logger.info( |
| f"Distributed environment: world size: {DIST_WRAPPER.world_size}, " |
| + f"global rank: {DIST_WRAPPER.rank}, local rank: {DIST_WRAPPER.local_rank}" |
| ) |
| device = torch.device("cuda:{}".format(DIST_WRAPPER.local_rank)) |
| torch.cuda.set_device(device) |
| if DIST_WRAPPER.world_size > 1: |
| dist.init_process_group(backend="nccl") |
|
|
| |
| infer_dl = get_inference_dataloader(configs=configs) |
|
|
| |
| model = ODesign(configs).to(device) |
|
|
| |
| dumper = DataDumper(base_dir=dump_dir) |
|
|
| |
| infer_runner = InferRunner( |
| configs=configs, |
| dump_dir=dump_dir, |
| error_dir=error_dir, |
| device=device, |
| infer_dl=infer_dl, |
| model=model, |
| dumper=dumper, |
| ) |
|
|
| infer_runner.run() |
| |
|
|
| if __name__ == "__main__": |
| main() |
|
|
