def default_setup(cfg, args):
output_dir = cfg.OUTPUT_DIR
if output_dir:
mkdir(output_dir)
rank = comm.get_rank()
logger = setup_logger(output_dir, rank)
logger.info("Using {} GPUs".format(args.num_gpus))
logger.info("Collecting environment info")
logger.info("\n" + collect_env_info())
logger.info(args)
logger.info("Loaded configuration file {}".format(args.config_file))
with open(args.config_file, "r") as cf:
config_str = "\n" + cf.read()
logger.info(config_str)
logger.info("Running with config:\n{}".format(cfg))
# make sure each worker has a different, yet deterministic seed if specified
seed_all_rng(None if cfg.SEED < 0 else cfg.SEED + rank)
# cudnn benchmark has large overhead. It shouldn't be used considering the small size of
# typical validation set.
if not (hasattr(args, "eval_only") and args.eval_only):
torch.backends.cudnn.benchmark = cfg.CUDNN_BENCHMARK
def worker_init_reset_seed(worker_id):
seed_all_rng(np.random.randint(2 ** 31) + worker_id)