def configure_bbox_reg_weights(model, saved_cfg):
    """Compatibility for old models trained with bounding box regression
    mean/std normalization (instead of fixed weights).
    """
    if 'MODEL' not in saved_cfg or 'BBOX_REG_WEIGHTS' not in saved_cfg.MODEL:
        logger.warning('Model from weights file was trained before config key '
                       'MODEL.BBOX_REG_WEIGHTS was added. Forcing '
                       'MODEL.BBOX_REG_WEIGHTS = (1., 1., 1., 1.) to ensure '
                       'correct **inference** behavior.')
        # Generally we don't allow modifying the config, but this is a one-off
        # hack to support some very old models
        is_immutable = cfg.is_immutable()
        cfg.immutable(False)
        cfg.MODEL.BBOX_REG_WEIGHTS = (1., 1., 1., 1.)
        cfg.immutable(is_immutable)
        logger.info('New config:')
        logger.info(pprint.pformat(cfg))
        assert not model.train, (
            'This model was trained with an older version of the code that '
            'used bounding box regression mean/std normalization. It can no '
            'longer be used for training. To upgrade it to a trainable model '
            'please use fb/compat/convert_bbox_reg_normalized_model.py.'
        )
Compatibility for old models trained with bounding box regression
    mean/std normalization (instead of fixed weights).
    
detectron/utils/net.py