How to use the skorch.utils.noop function in skorch

def _default_callbacks(self):
        return [
            ('epoch_timer', EpochTimer()),
            ('train_loss', BatchScoring(
                train_loss_score,
                name='train_loss',
                on_train=True,
                target_extractor=noop,
            )),
            ('valid_loss', BatchScoring(
                valid_loss_score,
                name='valid_loss',
                target_extractor=noop,
            )),
            ('valid_acc', EpochScoring(
                'accuracy',
                name='valid_acc',
                lower_is_better=False,
            )),
            ('print_log', PrintLog()),
        ]

def _default_callbacks(self):
        return [
            ('epoch_timer', EpochTimer()),
            ('train_loss', BatchScoring(
                train_loss_score,
                name='train_loss',
                on_train=True,
                target_extractor=noop,
            )),
            ('valid_loss', BatchScoring(
                valid_loss_score,
                name='valid_loss',
                target_extractor=noop,
            )),
            ('print_log', PrintLog()),
        ]

def _default_callbacks(self):
        return [
            ('epoch_timer', EpochTimer()),
            ('train_loss', BatchScoring(
                train_loss_score,
                name='train_loss',
                on_train=True,
                target_extractor=noop,
            )),
            ('valid_loss', BatchScoring(
                valid_loss_score,
                name='valid_loss',
                target_extractor=noop,
            )),
            ('print_log', PrintLog()),
        ]

def _default_callbacks(self):
        return [
            ('epoch_timer', EpochTimer()),
            ('train_loss', BatchScoring(
                train_loss_score,
                name='train_loss',
                on_train=True,
                target_extractor=noop,
            )),
            ('valid_loss', BatchScoring(
                valid_loss_score,
                name='valid_loss',
                target_extractor=noop,
            )),
            ('valid_acc', EpochScoring(
                'accuracy',
                name='valid_acc',
                lower_is_better=False,
            )),
            ('print_log', PrintLog()),
        ]

    def __init__(self, patterns, fn=noop, at=1, schedule=None):
        self.at = at
        self.fn = fn
        self.schedule = schedule
        self.patterns = patterns

def __init__(
            self,
            monitor='valid_loss_best',
            f_params='params.pt',
            f_optimizer='optimizer.pt',
            f_history='history.json',
            f_pickle=None,
            fn_prefix='',
            dirname='',
            event_name='event_cp',
            sink=noop,
    ):
        self.monitor = monitor
        self.f_params = f_params
        self.f_optimizer = f_optimizer
        self.f_history = f_history
        self.f_pickle = f_pickle
        self.fn_prefix = fn_prefix
        self.dirname = dirname
        self.event_name = event_name
        self.sink = sink
        self._validate_filenames()

def _default_schedule(self, net):
        if self.at(net):
            return self.fn
        return noop

def _default_callbacks(self):
        return [
            ('epoch_timer', EpochTimer()),
            ('train_loss', BatchScoring(
                train_loss_score,
                name='train_loss',
                on_train=True,
                target_extractor=noop,
            )),
            ('valid_loss', BatchScoring(
                valid_loss_score,
                name='valid_loss',
                target_extractor=noop,
            )),
            ('print_log', PrintLog()),
        ]

def _default_callbacks(self):
        return [
            ('epoch_timer', EpochTimer()),
            ('train_loss', BatchScoring(
                train_loss_score,
                name='train_loss',
                on_train=True,
                target_extractor=noop,
            )),
            ('valid_loss', BatchScoring(
                valid_loss_score,
                name='valid_loss',
                target_extractor=noop,
            )),
            ('print_log', PrintLog()),
        ]