def compute_loss_and_decoded_output(
        self, masked_adv_input: "torch.Tensor", original_output: np.ndarray, **kwargs
    ) -> tuple["torch.Tensor", np.ndarray]:
        """
        Compute loss function and decoded output.

        :param masked_adv_input: The perturbed inputs.
        :param original_output: Target values of shape (nb_samples). Each sample in `original_output` is a string, and
                                it may possess different lengths. A possible example of `original_output` could be:
                                `original_output = np.array(['SIXTY ONE', 'HELLO'])`.
        :return: The loss and the decoded output.
        """
        raise NotImplementedError

        Compute loss function and decoded output.

        :param masked_adv_input: The perturbed inputs.
        :param original_output: Target values of shape (nb_samples). Each sample in `original_output` is a string, and
                                it may possess different lengths. A possible example of `original_output` could be:
                                `original_output = np.array(['SIXTY ONE', 'HELLO'])`.
        :return: The loss and the decoded output.
        
art/estimators/speech_recognition/speech_recognizer.py