def __init__(self, *args, **kwargs):
        super(UncertaintySampling, self).__init__(*args, **kwargs)

        self.model = kwargs.pop('model', None)
        if self.model is None:
            raise TypeError(
                "__init__() missing required keyword-only argument: 'model'"
                )
        if not isinstance(self.model, ContinuousModel):
            raise TypeError(
                "model has to be a ContinuousModel"
                )
        self.model.train(self.dataset)

        self.method = kwargs.pop('method', 'lc')
        if self.method not in ['lc', 'sm']:
            raise TypeError(
                "supported methods are ['lc', 'sm'], the given one is: " + \
                self.method
                )
dataset/ETHPy150Open ntucllab/libact/libact/query_strategies/uncertainty_sampling.py/UncertaintySampling.__init__/original