tools/train.py

import os.path as osp
import logging
import warnings
import sys

from detectron2.checkpoint import DetectionCheckpointer
from detectron2.config import LazyConfig, instantiate
from detectron2.engine import (
    default_argument_parser,
    default_setup,
    default_writers,
    hooks,
    launch,
)
from detectron2.engine.defaults import create_ddp_model
from detectron2.utils import comm


sys.path.append(osp.dirname(osp.dirname(__file__)))
warnings.filterwarnings("ignore")
logger = logging.getLogger("detectron2")


from engine import CycleTrainer


def do_train(args, cfg):
    """
    Args:
        cfg: an object with the following attributes:
            model: instantiate to a module
            dataloader.{train,test}: instantiate to dataloaders
            dataloader.evaluator: instantiate to evaluator for test set
            optimizer: instantaite to an optimizer
            lr_multiplier: instantiate to a fvcore scheduler
            train: other misc config defined in `configs/common/train.py`, including:
                output_dir (str)
                init_checkpoint (str)
                amp.enabled (bool)
                max_iter (int)
                eval_period, log_period (int)
                device (str)
                checkpointer (dict)
                ddp (dict)
    """
    model = instantiate(cfg.model)
    logger = logging.getLogger("detectron2")
    logger.info("Model:\n{}".format(model))
    model.to(cfg.train.device)

    cfg.optimizer.params.model = model
    optim = instantiate(cfg.optimizer)

    train_loader = instantiate(cfg.dataloader.train)

    model = create_ddp_model(model, **cfg.train.ddp)
    trainer = CycleTrainer(model, train_loader, optim)
    checkpointer = DetectionCheckpointer(
        model,
        cfg.train.output_dir,
        trainer=trainer,
    )
    trainer.register_hooks(
        [
            hooks.IterationTimer(),
            hooks.LRScheduler(scheduler=instantiate(cfg.lr_multiplier)),
            hooks.PeriodicCheckpointer(checkpointer, **cfg.train.checkpointer)
            if comm.is_main_process()
            else None,
            # hooks.EvalHook(cfg.train.eval_period, lambda: do_test(cfg, model)),
            hooks.PeriodicWriter(
                default_writers(cfg.train.output_dir, cfg.train.max_iter),
                period=cfg.train.log_period,
            )
            if comm.is_main_process()
            else None,
        ]
    )

    checkpointer.resume_or_load(cfg.train.init_checkpoint, resume=args.resume)
    if args.resume and checkpointer.has_checkpoint():
        start_iter = trainer.iter + 1
    else:
        start_iter = 0
    trainer.train(start_iter, cfg.train.max_iter)


def main(args):
    cfg = LazyConfig.load(args.config_file)
    cfg = LazyConfig.apply_overrides(cfg, args.opts)
    default_setup(cfg, args)
    do_train(args, cfg)


if __name__ == "__main__":
    args = default_argument_parser().parse_args()
    launch(
        main,
        args.num_gpus,
        num_machines=args.num_machines,
        machine_rank=args.machine_rank,
        dist_url=args.dist_url,
        args=(args,),
    )