train_net.py

from detectron2.engine import default_argument_parser, launch
import detectron2.utils.comm as comm
from detectron2.evaluation import verify_results
from detectron2.checkpoint import DetectionCheckpointer
from pgrcnn.utils.launch_utils import setup, Trainer

def main(args):
    checkpointable = args.resume

    cfg = setup(args)

    if args.eval_only:
        model = Trainer.build_model(cfg)
        DetectionCheckpointer(model, save_dir=cfg.OUTPUT_DIR).resume_or_load(
            cfg.MODEL.WEIGHTS, resume=args.resume
        )
        res = Trainer.test(cfg, model)
        if cfg.TEST.AUG.ENABLED:
            res.update(Trainer.test_with_TTA(cfg, model))
        if comm.is_main_process():
            verify_results(cfg, res)
        return res

    trainer = Trainer(cfg)

    # checkpointable = False
    trainer.resume_or_load(resume=args.resume, checkpointable=checkpointable)
    return trainer.train()


if __name__ == "__main__":
    args = default_argument_parser().parse_args()
    # lazy add config file
    # args.num_gpus = 1
    # args.config_file = "configs/pg_rcnn_R_50_FPN_1x_test_2.yaml"
    # args.eval_only = True
    # args.resume = False
    launch(
        main,
        args.num_gpus,
        num_machines=args.num_machines,
        machine_rank=args.machine_rank,
        dist_url=args.dist_url,
        args=(args,),
    )