def fit(
        self,
        series: Union[TimeSeries, Sequence[TimeSeries]],
    ) -> Self:
        """Fits the scorer on the given time series.

        If a sequence of series, the scorer is fitted on the concatenation of the sequence.

        The assumption is that `series` is generally anomaly-free.

        Parameters
        ----------
        series
            The (sequence of) series with no anomalies.

        Returns
        -------
        self
            Fitted Scorer.
        """
        width = series2seq(series)[0].width
        series = _check_input(
            series,
            name="series",
            width_expected=width,
            extra_checks=self._check_window_size,
        )
        self.width_trained_on = width
        self._fit_core(series)
        self._fit_called = True
        return self
Fits the scorer on the given time series.

        If a sequence of series, the scorer is fitted on the concatenation of the sequence.

        The assumption is that `series` is generally anomaly-free.

        Parameters
        ----------
        series
            The (sequence of) series with no anomalies.

        Returns
        -------
        self
            Fitted Scorer.
        
darts/ad/scorers/scorers.py