def __call__(self, *args, **kwargs):
        """
        Forwards the `audio` and `sampling_rate` arguments to [`~ClvpFeatureExtractor.__call__`] and the `text`
        argument to [`~ClvpTokenizer.__call__`]. Please refer to the doctsring of the above two methods for more
        information.
        """

        raw_speech = kwargs.pop("raw_speech", None)
        sampling_rate = kwargs.pop("sampling_rate", None)
        text = kwargs.pop("text", None)

        if raw_speech is None and text is None:
            raise ValueError("You need to specify either an `raw_speech` or `text` input to process.")

        if raw_speech is not None:
            inputs = self.feature_extractor(raw_speech, sampling_rate=sampling_rate, **kwargs)
        if text is not None:
            encodings = self.tokenizer(text, **kwargs)

        if text is None:
            return inputs
        elif raw_speech is None:
            return encodings
        else:
            inputs["input_ids"] = encodings["input_ids"]
            inputs["attention_mask"] = encodings["attention_mask"]
            return inputs

        Forwards the `audio` and `sampling_rate` arguments to [`~ClvpFeatureExtractor.__call__`] and the `text`
        argument to [`~ClvpTokenizer.__call__`]. Please refer to the doctsring of the above two methods for more
        information.
        
dpkd/transformers/src/transformers/models/clvp/processing_clvp.py