def test_use_static_covariates(self, model_cls, ts):
        """
        Check that both static covariates representations are supported (component-specific and shared)
        for both uni- and multivariate series when fitting the model.
        Also check that the static covariates are present in the forecasted series
        """
        model = model_cls(
            input_chunk_length=IN_LEN,
            output_chunk_length=OUT_LEN,
            random_state=0,
            use_static_covariates=True,
            n_epochs=1,
            **tfm_kwargs,
        )
        # must provide mandatory future_covariates to TFTModel
        model.fit(
            series=ts,
            future_covariates=(
                self.sine_1_ts if model.supports_future_covariates else None
            ),
        )
        pred = model.predict(OUT_LEN)
        assert pred.static_covariates.equals(ts.static_covariates)

        Check that both static covariates representations are supported (component-specific and shared)
        for both uni- and multivariate series when fitting the model.
        Also check that the static covariates are present in the forecasted series
        
darts/tests/models/forecasting/test_global_forecasting_models.py