Function main

evaluate_joint.py:295–464

()

def main():
    args = parse_args()

    accelerator_log_kwargs = {}

    accelerator = Accelerator(**accelerator_log_kwargs)
    
    # Make one log on every process with the configuration for debugging.
    if accelerator.is_local_main_process:
        datasets.utils.logging.set_verbosity_warning()
        transformers.utils.logging.set_verbosity_info()
        log_level = logging.INFO
    else:
        datasets.utils.logging.set_verbosity_error()
        transformers.utils.logging.set_verbosity_error()
        log_level = logging.ERROR

    logger.remove()
    logger.add(sys.stdout, format = "<green>{time:YYYY-MM-DD HH:mm:ss}</green> | <level>{level}</level> | <blue>{process.name}</blue> | <cyan>{name}</cyan>:<cyan>{function}</cyan>:<cyan>{line}</cyan> - <level>{message}</level>", level=log_level)

    # Intercept default logging and transform to loguru
    class InterceptHandler(logging.Handler):
        def emit(self, record: logging.LogRecord) -> None:
            # Get corresponding Loguru level if it exists.
            level: str | int
            try:
                level = logger.level(record.levelname).name
            except ValueError:
                level = record.levelno

            # Find caller from where originated the logged message.
            frame, depth = inspect.currentframe(), 0
            while frame and (depth == 0 or frame.f_code.co_filename == logging.__file__):
                frame = frame.f_back
                depth += 1

            logger.opt(depth=depth, exception=record.exc_info).log(level, record.getMessage())

    logging.basicConfig(handlers=[InterceptHandler()], level=log_level, force=True)
    transformers.utils.logging.disable_default_handler()
    transformers.utils.logging.add_handler(InterceptHandler())
    logger.info(f"{accelerator.state}")

    # If passed along, set the training seed now.
    if args.seed is not None:
        set_seed(args.seed)

    # -------------------------------------------------Load Dataset and Model------------------------------------------------------------
    # Load config and model
    if args.config_name:
        config = AutoConfig.from_pretrained(
            args.config_name,
            trust_remote_code=args.trust_remote_code,
        )
    elif args.model_name_or_path:
        config = AutoConfig.from_pretrained(
            args.model_name_or_path,
            trust_remote_code=args.trust_remote_code,