def process(self, inputs, outputs):
        """
        Args:
            inputs: the inputs to a COCO model (e.g., GeneralizedRCNN).
                It is a list of dict. Each dict corresponds to an image and
                contains keys like "height", "width", "file_name", "image_id".
            outputs: the outputs of a COCO model. It is a list of dicts with key
                "instances" that contains :class:`Instances`.
        """
        for output in outputs:
            self._text_ids.extend(output['caption']['caption_ids'])
            self._image_ids.append(output['caption']['image_ids'])
            self._text_embeds.append(output['caption']['text_embeds'])
            self._image_embeds.append(output['caption']['image_embeds'][0])
            if self._ensemble:
                self._image_embeds2.append(output['caption']['image_embeds'][1])

        Args:
            inputs: the inputs to a COCO model (e.g., GeneralizedRCNN).
                It is a list of dict. Each dict corresponds to an image and
                contains keys like "height", "width", "file_name", "image_id".
            outputs: the outputs of a COCO model. It is a list of dicts with key
                "instances" that contains :class:`Instances`.
        
datasets/evaluation/retrieval_evaluation.py