def _sanity_check_predict_likelihood_parameters(
        self, n: int, output_chunk_length: Union[int, None], num_samples: int
    ):
        """Verify that the assumptions for likelihood parameters prediction are verified:
        - Probabilistic models fitted with a likelihood
        - `num_samples=1`
        - `n <= output_chunk_length`
        """
        if not self.supports_likelihood_parameter_prediction:
            raise_log(
                ValueError(
                    "`predict_likelihood_parameters=True` is only supported for probabilistic models fitted with "
                    "a likelihood."
                ),
                logger,
            )
        if num_samples != 1:
            raise_log(
                ValueError(
                    f"`predict_likelihood_parameters=True` is only supported for `num_samples=1`, "
                    f"received {num_samples}."
                ),
                logger,
            )
        if output_chunk_length is not None and n > output_chunk_length:
            raise_log(
                ValueError(
                    "`predict_likelihood_parameters=True` is only supported for `n` smaller than or equal to "
                    "`output_chunk_length`."
                ),
                logger,
            )
Verify that the assumptions for likelihood parameters prediction are verified:
        - Probabilistic models fitted with a likelihood
        - `num_samples=1`
        - `n <= output_chunk_length`
        
darts/models/forecasting/forecasting_model.py