` and `text_embeds`. This represents the audio-text
            similarity scores.
        logits_per_text:(`torch.FloatTensor` of shape `(text_batch_size, audio_batch_size)`):
            The scaled dot product scores between `text_embeds` and `audio_embeds`. This represents the text-audio
            similarity scores.
        text_embeds(`torch.FloatTensor` of shape `(batch_size, output_dim`):
            The text embeddings obtained by applying the projection layer to the pooled output of [`ClapTextModel`].
        audio_embeds(`torch.FloatTensor` of shape `(batch_size, output_dim`):
            The audio embeddings obtained by applying the projection layer to the pooled output of [`ClapAudioModel`].
        text_model_output(`BaseModelOutputWithPooling`):
            The output of the [`ClapTextModel`].
        audio_model_output(`BaseModelOutputWithPooling`):
            The output of the [`ClapAudioModel`].
    N