def log_audio(self, key: str, audios: list[Any], step: Optional[int] = None, **kwargs: Any) -> None:
        r"""Log audios (numpy arrays, or file paths).

        Args:
            key: The key to be used for logging the audio files
            audios: The list of audio file paths, or numpy arrays to be logged
            step: The step number to be used for logging the audio files
            \**kwargs: Optional kwargs are lists passed to each ``Wandb.Audio`` instance (ex: caption, sample_rate).

        Optional kwargs are lists passed to each audio (ex: caption, sample_rate).

        """
        if not isinstance(audios, list):
            raise TypeError(f'Expected a list as "audios", found {type(audios)}')
        n = len(audios)
        for k, v in kwargs.items():
            if len(v) != n:
                raise ValueError(f"Expected {n} items but only found {len(v)} for {k}")
        kwarg_list = [{k: kwargs[k][i] for k in kwargs} for i in range(n)]

        import wandb

        metrics = {key: [wandb.Audio(audio, **kwarg) for audio, kwarg in zip(audios, kwarg_list)]}
        self.log_metrics(metrics, step)  # type: ignore[arg-type]
Log audios (numpy arrays, or file paths).

        Args:
            key: The key to be used for logging the audio files
            audios: The list of audio file paths, or numpy arrays to be logged
            step: The step number to be used for logging the audio files
            \**kwargs: Optional kwargs are lists passed to each ``Wandb.Audio`` instance (ex: caption, sample_rate).

        Optional kwargs are lists passed to each audio (ex: caption, sample_rate).

        
src/lightning/pytorch/loggers/wandb.py