How to use the pmdarima.utils.check_exog function in pmdarima

def _check_exog(self, exogenous):
        # if we fit with exog, make sure one was passed, or else fail out:
        if self.fit_with_exog_:
            if exogenous is None:
                raise ValueError('When an ARIMA is fit with an exogenous '
                                 'array, it must also be provided one for '
                                 'predicting or updating observations.')
            else:
                return check_exog(
                    exogenous, force_all_finite=True, dtype=DTYPE)
        return None

exogenous : array-like, shape=[n_obs, n_vars], optional (default=None)
            An optional 2-d array of exogenous variables. If provided, these
            variables are used as additional features in the regression
            operation. This should not include a constant or trend. Note that
            if an ``ARIMA`` is fit on exogenous features, it must be provided
            exogenous features for making predictions.

        **fit_args : dict or kwargs
            Any keyword arguments to pass to the statsmodels ARIMA fit.
        """
        y = check_endog(y, dtype=DTYPE)
        n_samples = y.shape[0]

        # if exog was included, check the array...
        if exogenous is not None:
            exogenous = check_exog(exogenous, force_all_finite=False,
                                   copy=False, dtype=DTYPE)

        # determine the CV args, if any
        cv = self.out_of_sample_size
        scoring = get_callable(self.scoring, VALID_SCORING)

        # don't allow negative, don't allow > n_samples
        cv = max(cv, 0)

        # if cv is too big, raise
        if cv >= n_samples:
            raise ValueError("out-of-sample size must be less than number "
                             "of samples!")

        # If we want to get a score on the out-of-sample, we need to trim
        # down the size of our y vec for fitting. Addressed due to Issue #28

def _check_y_exog(y, exog):
        """Validate input"""
        # Do not force finite, since a transformer's goal may be imputation.
        if y is not None:
            y = check_endog(y, dtype=DTYPE, copy=True, force_all_finite=False)

        if exog is not None:
            exog = check_exog(
                exog, dtype=DTYPE, copy=True, force_all_finite=False)
        return y, exog