def _get_params(
        self,
        transformer_selector: Iterable,
        series_specified: bool = False,
    ) -> Generator[Mapping[str, Any], None, None]:
        """
        Creates generator of dictionaries containing fixed parameter values
        (i.e. attributes defined in the child-most class). Those fixed parameters
        specified by `parallel_params` are given different values over each of the
        parallel jobs. Called by `transform` and `inverse_transform`,
        if `Transformer` does *not* inherit from `FittableTransformer`.
        """
        self._check_fixed_params(transformer_selector)

        def params_generator(transformer_selector, fixed_params, parallel_params):
            fixed_params_copy = fixed_params.copy()
            for i in transformer_selector:
                for key in parallel_params:
                    fixed_params_copy[key] = fixed_params[key][i]
                if fixed_params_copy:
                    params = {"fixed": fixed_params_copy}
                else:
                    params = None
                yield params
            return None

        return params_generator(
            transformer_selector, self._fixed_params, self._parallel_params
        )

        Creates generator of dictionaries containing fixed parameter values
        (i.e. attributes defined in the child-most class). Those fixed parameters
        specified by `parallel_params` are given different values over each of the
        parallel jobs. Called by `transform` and `inverse_transform`,
        if `Transformer` does *not* inherit from `FittableTransformer`.
        
darts/dataprocessing/transformers/base_data_transformer.py