def forward(self, feats, img_metas):
        """
        Args:
            feats (list[Tensor]): Feature maps of each level. Each has
                shape of [bs, c, h, w].
            img_metas (list[dict]): List of image information. Pass in
                for creating more accurate padding mask. #! not used here.

        Returns:
            tuple: a tuple containing the following:

                - mask_feature (Tensor): Shape [bs, c, h, w].
                - memory (Tensor): Output of last stage of backbone.
                    Shape [bs, c, h, w].
        """
        y = self.last_feat_conv(feats[-1])
        for i in range(self.num_inputs - 2, -1, -1):
            x = feats[i]
            cur_fpn = self.lateral_convs[i](x)
            y = cur_fpn + \
                F.interpolate(y, size=cur_fpn.shape[-2:], mode='nearest')
            y = self.output_convs[i](y)

        mask_feature = self.mask_feature(y)
        memory = feats[-1]
        return mask_feature, memory

        Args:
            feats (list[Tensor]): Feature maps of each level. Each has
                shape of [bs, c, h, w].
            img_metas (list[dict]): List of image information. Pass in
                for creating more accurate padding mask. #! not used here.

        Returns:
            tuple: a tuple containing the following:

                - mask_feature (Tensor): Shape [bs, c, h, w].
                - memory (Tensor): Output of last stage of backbone.
                    Shape [bs, c, h, w].
        
EVA-01/seg/mmseg_custom/models/plugins/pixel_decoder.py