def class_predictor(
        self,
        image_feats: torch.FloatTensor,
        query_embeds: Optional[torch.FloatTensor] = None,
        query_mask: Optional[torch.Tensor] = None,
    ) -> Tuple[torch.FloatTensor]:
        """
        Args:
            image_feats:
                Features extracted from the `image_text_embedder`.
            query_embeds:
                Text query embeddings.
            query_mask:
                Must be provided with query_embeddings. A mask indicating which query embeddings are valid.
        """
        (pred_logits, image_class_embeds) = self.class_head(image_feats, query_embeds, query_mask)

        return (pred_logits, image_class_embeds)

        Args:
            image_feats:
                Features extracted from the `image_text_embedder`.
            query_embeds:
                Text query embeddings.
            query_mask:
                Must be provided with query_embeddings. A mask indicating which query embeddings are valid.
        
dpkd/transformers/src/transformers/models/owlvit/modeling_owlvit.py