def _verify_passed_predict_covariates(self, future_covariates: TimeSeries):
        """Simple check if user supplied/did not supply covariates as done at fitting time."""
        if self.uses_future_covariates:
            # at this point future covariates are available, either passed from user or retrieved from
            # covariates used during training
            if (
                future_covariates.n_components
                != self.future_covariate_series.n_components
            ):
                n_expected = self.future_covariate_series.n_components
                n_actual = future_covariates.n_components
                if self.encoders is not None and self.encoders.encoding_available:
                    n_encodings = self.encoders.encoding_n_components[1]
                    n_expected -= n_encodings
                    n_actual -= n_encodings
                raise_log(
                    ValueError(
                        f"The `future_covariates` passed to `predict()` must have the same number "
                        f"of components / columns as the `future_covariates` used to train the model. "
                        f"Received number of components `{n_actual}`, excepted {n_expected}."
                    )
                )
        elif future_covariates is not None:
            raise_log(
                ValueError(
                    "The model was trained without future covariates, but future `future_covariates` "
                    "were provided to `predict()`."
                )
            )
Simple check if user supplied/did not supply covariates as done at fitting time.
darts/models/forecasting/forecasting_model.py