本文整理匯總了Python中detectron.core.config.cfg.is_immutable方法的典型用法代碼示例。如果您正苦於以下問題：Python cfg.is_immutable方法的具體用法？Python cfg.is_immutable怎麽用？Python cfg.is_immutable使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類detectron.core.config.cfg的用法示例。
在下文中一共展示了cfg.is_immutable方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: configure_bbox_reg_weights
# 需要導入模塊: from detectron.core.config import cfg [as 別名]
# 或者: from detectron.core.config.cfg import is_immutable [as 別名]
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.'
)