import argparse
import datetime
import importlib
import os
from shutil import copyfile

import torch
import torch.distributed as dist
from omegaconf import OmegaConf

from utils.dist_utils import (
    get_world_size,
)
from utils.utils import seed_all


parser = argparse.ArgumentParser(description="VFI")
parser.add_argument("-c", "--config", type=str)
parser.add_argument("-p", "--port", default="23455", type=str)
parser.add_argument("--local_rank", default="0")

args = parser.parse_args()


def main_worker(rank, config):
    if "local_rank" not in config:
        config["local_rank"] = config["global_rank"] = rank
    if torch.cuda.is_available():
        print(f"Rank {rank} is available")
        config["device"] = f"cuda:{rank}"
        if config["distributed"]:
            dist.init_process_group(backend="nccl", timeout=datetime.timedelta(seconds=5400))
    else:
        config["device"] = "cpu"

    cfg_name = os.path.basename(args.config).split(".")[0]
    config["exp_name"] = cfg_name + "_" + config["exp_name"]
    config["save_dir"] = os.path.join(config["save_dir"], config["exp_name"])

    if (not config["distributed"]) or rank == 0:
        os.makedirs(config["save_dir"], exist_ok=True)
        os.makedirs(f"{config['save_dir']}/ckpts", exist_ok=True)
        config_path = os.path.join(config["save_dir"], args.config.split("/")[-1])
        if not os.path.isfile(config_path):
            copyfile(args.config, config_path)
        print("[**] create folder {}".format(config["save_dir"]))

    trainer_name = config.get("trainer_type", "base_trainer")
    print(f"using GPU {rank} for training")
    if rank == 0:
        print(trainer_name)
    trainer_pack = importlib.import_module("trainers." + trainer_name)
    trainer = trainer_pack.Trainer(config)

    trainer.train()


if __name__ == "__main__":
    torch.backends.cudnn.benchmark = True
    cfg = OmegaConf.load(args.config)
    seed_all(cfg.seed)
    rank = int(args.local_rank)
    torch.cuda.set_device(torch.device(f"cuda:{rank}"))
    # setting distributed cfgurations
    cfg["world_size"] = get_world_size()
    cfg["local_rank"] = rank
    if rank == 0:
        print("world_size: ", cfg["world_size"])
    main_worker(rank, cfg)