def _name_mapping(self) -> dict[str, str]:
        """Returns the feature name mapping of the TFT model.

        Returns
        -------
        Dict[str, str]
            The feature name mapping. For example
            {
                'target_0': 'ice cream',
                'past_covariate_0': 'heater',
                'past_covariate_1': 'year',
                'past_covariate_2': 'month',
                'future_covariate_0': 'darts_enc_fc_cyc_month_sin',
                'future_covariate_1': 'darts_enc_fc_cyc_month_cos',
             }
        """

        def map_cols(comps, name, suffix):
            comps = comps if comps is not None else []
            return {
                f"{name}_{i}": colname + f"_{suffix}" for i, colname in enumerate(comps)
            }

        return {
            **map_cols(self.target_components, "target", "target"),
            **map_cols(
                self.static_covariates_components, "static_covariate", "statcov"
            ),
            **map_cols(self.past_covariates_components, "past_covariate", "pastcov"),
            **map_cols(self.future_covariates_components, "future_covariate", "futcov"),
        }
Returns the feature name mapping of the TFT model.

        Returns
        -------
        Dict[str, str]
            The feature name mapping. For example
            {
                'target_0': 'ice cream',
                'past_covariate_0': 'heater',
                'past_covariate_1': 'year',
                'past_covariate_2': 'month',
                'future_covariate_0': 'darts_enc_fc_cyc_month_sin',
                'future_covariate_1': 'darts_enc_fc_cyc_month_cos',
             }
        
darts/explainability/tft_explainer.py