def predict_likelihood_parameters(self, model_output: torch.Tensor) -> torch.Tensor:
        """
        Returns the distribution parameters as a single Tensor, extracted from the raw model outputs.
        """
        params = self._params_from_output(model_output)
        if isinstance(params, torch.Tensor):
            return params
        else:
            # interleave the predicted parameters to group them by input series component
            num_samples, n_times, n_components, n_params = model_output.shape
            return torch.stack(params, dim=3).reshape((
                num_samples,
                n_times,
                n_components * n_params,
            ))

        Returns the distribution parameters as a single Tensor, extracted from the raw model outputs.
        
darts/utils/likelihood_models/torch.py