def _get_params(
        self,
        transformer_selector: Iterable,
        calling_fit: bool = False,
        series_specified: bool = False,
    ) -> Generator[Mapping[str, Any], None, None]:
        """
        Overrides `_get_params` of `BaseDataTransformer`. Creates generator of dictionaries containing
        both the fixed parameter values (i.e. attributes defined in the child-most class), as well as
        the fitted parameter values (only if `calling_fit = False`). Those fixed parameters
        specified by `parallel_params` are given different values over each of the parallel jobs;
        every fitted parameter is given a different value for each parallel job (since `self.fit`
        returns a `Sequence` containing one fitted parameter value of each parallel job). Called by
        `transform` and `inverse_transform`.
        """
        # Call `_check_fixed_params` of `BaseDataTransformer`:
        self._check_fixed_params(transformer_selector)
        fitted_params = self._get_fitted_params(
            transformer_selector, calling_fit, series_specified=series_specified
        )

        def params_generator(
            transformer_selector_,
            fixed_params,
            fitted_params,
            parallel_params,
            global_fit,
        ):
            fixed_params_copy = fixed_params.copy()
            for i in transformer_selector_:
                for key in parallel_params:
                    fixed_params_copy[key] = fixed_params[key][i]
                params = {}
                if fixed_params_copy:
                    params["fixed"] = fixed_params_copy
                if fitted_params:
                    params["fitted"] = (
                        fitted_params[0] if global_fit else fitted_params[i]
                    )
                if not params:
                    params = None
                yield params

        transformer_selector_ = (
            transformer_selector if not (calling_fit and self._global_fit) else [0]
        )

        return params_generator(
            transformer_selector_,
            self._fixed_params,
            fitted_params,
            self._parallel_params,
            self._global_fit,
        )

        Overrides `_get_params` of `BaseDataTransformer`. Creates generator of dictionaries containing
        both the fixed parameter values (i.e. attributes defined in the child-most class), as well as
        the fitted parameter values (only if `calling_fit = False`). Those fixed parameters
        specified by `parallel_params` are given different values over each of the parallel jobs;
        every fitted parameter is given a different value for each parallel job (since `self.fit`
        returns a `Sequence` containing one fitted parameter value of each parallel job). Called by
        `transform` and `inverse_transform`.
        
darts/dataprocessing/transformers/fittable_data_transformer.py