    def get_audio_embedding(self, data):
        """Get the audio embedding from the model

        Parameters
        ----------
        data: a list of dict
            the audio input dict list from 'get_audio_feature' method

        Returns
        ----------
        audio_embed: torch.Tensor
            a tensor of audio_embeds (N, D)

        """
        device = next(self.parameters()).device
        input_dict = {}
        keys = data[0].keys()
        for k in keys:
            input_dict[k] = torch.cat([d[k].unsqueeze(0) for d in data], dim=0).to(
                device
            )

        audio_embeds = self.audio_projection(
            self.encode_audio(input_dict, device=device)["embedding"]
        )
        audio_embeds = F.normalize(audio_embeds, dim=-1)

        return audio_embeds
Get the audio embedding from the model

Parameters
----------
data: a list of dict
the audio input dict list from 'get_audio_feature' method

Returns
----------
audio_embed: torch.Tensor
a tensor of audio_embeds (N, D)
models/tta/picoaudio/picoaudio/audioldm/clap/open_clip/model.py