def __init__(self, period, model, data_loader, num_iter):
        """
        Args:
            period (int): the period this hook is run, or 0 to not run during training.
                The hook will always run in the end of training.
            model (nn.Module): a module whose all BN layers in training mode will be
                updated by precise BN.
                Note that user is responsible for ensuring the BN layers to be
                updated are in training mode when this hook is triggered.
            data_loader (iterable): it will produce data to be run by `model(data)`.
            num_iter (int): number of iterations used to compute the precise
                statistics.
        """
        self._logger = logging.getLogger(__name__)
        if len(get_bn_modules(model)) == 0:
            self._logger.info(
                "PreciseBN is disabled because model does not contain BN layers in training mode."
            )
            self._disabled = True
            return

        self._model = model
        self._data_loader = data_loader
        self._num_iter = num_iter
        self._period = period
        self._disabled = False

        self._data_iter = None

        Args:
            period (int): the period this hook is run, or 0 to not run during training.
                The hook will always run in the end of training.
            model (nn.Module): a module whose all BN layers in training mode will be
                updated by precise BN.
                Note that user is responsible for ensuring the BN layers to be
                updated are in training mode when this hook is triggered.
            data_loader (iterable): it will produce data to be run by `model(data)`.
            num_iter (int): number of iterations used to compute the precise
                statistics.
        
video_chat_with_ChatGPT/models/grit_src/third_party/CenterNet2/detectron2/engine/hooks.py