def forward(self, feats: Tuple[Tensor]) -> Tuple[Tensor, Tensor]:
        """Forward the network.

        The input is the featuremap extracted by backbone and the
        output is the simcc representation.

        Args:
            feats (Tuple[Tensor]): Multi scale feature maps.

        Returns:
            pred_x (Tensor): 1d representation of x.
            pred_y (Tensor): 1d representation of y.
        """
        feats = feats[-1]

        feats = self.final_layer(feats)  # -> B, K, H, W

        # flatten the output heatmap
        feats = torch.flatten(feats, 2)

        feats = self.mlp(feats)  # -> B, K, hidden

        feats = self.gau(feats)

        pred_x = self.cls_x(feats)
        pred_y = self.cls_y(feats)

        return pred_x, pred_y
Forward the network.

        The input is the featuremap extracted by backbone and the
        output is the simcc representation.

        Args:
            feats (Tuple[Tensor]): Multi scale feature maps.

        Returns:
            pred_x (Tensor): 1d representation of x.
            pred_y (Tensor): 1d representation of y.
        
mmpose/mmpose/models/heads/coord_cls_heads/rtmcc_head.py