def _caffe2_preprocess_image(self, inputs):
        """
        Caffe2 implementation of preprocess_image, which is called inside each MetaArch's forward.
        It normalizes the input images, and the final caffe2 graph assumes the
        inputs have been batched already.
        """
        data, im_info = inputs
        data = alias(data, "data")
        im_info = alias(im_info, "im_info")
        mean, std = self._wrapped_model.pixel_mean, self._wrapped_model.pixel_std
        normalized_data = (data - mean) / std
        normalized_data = alias(normalized_data, "normalized_data")

        # Pack (data, im_info) into ImageList which is recognized by self.inference.
        images = ImageList(tensor=normalized_data, image_sizes=im_info)
        return images

        Caffe2 implementation of preprocess_image, which is called inside each MetaArch's forward.
        It normalizes the input images, and the final caffe2 graph assumes the
        inputs have been batched already.
        
EVA-02/det/detectron2/export/caffe2_modeling.py