| | import os |
| | import argparse |
| | from shutil import copyfile |
| | import torch.distributed as dist |
| | import torch |
| | import importlib |
| | import datetime |
| | from utils.dist_utils import ( |
| | get_world_size, |
| | ) |
| | from omegaconf import OmegaConf |
| | 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}')) |
| | |
| | cfg['world_size'] = get_world_size() |
| | cfg['local_rank'] = rank |
| | if rank == 0: |
| | print('world_size: ', cfg['world_size']) |
| | main_worker(rank, cfg) |
| | |
| |
|
