def forward(self,
                xyz: torch.Tensor,
                new_xyz: torch.Tensor,
                features: torch.Tensor = None):
        """
        Args:
            xyz (Tensor): (B, N, 3) xyz coordinates of the features.
            new_xyz (Tensor): new xyz coordinates of the features.
            features (Tensor): (B, C, N) features to group.

        Returns:
            Tensor: (B, C + 3, 1, N) Grouped feature.
        """
        grouped_xyz = xyz.transpose(1, 2).unsqueeze(2)
        if features is not None:
            grouped_features = features.unsqueeze(2)
            if self.use_xyz:
                # (B, 3 + C, 1, N)
                new_features = torch.cat([grouped_xyz, grouped_features],
                                         dim=1)
            else:
                new_features = grouped_features
        else:
            new_features = grouped_xyz

        return new_features

        Args:
            xyz (Tensor): (B, N, 3) xyz coordinates of the features.
            new_xyz (Tensor): new xyz coordinates of the features.
            features (Tensor): (B, C, N) features to group.

        Returns:
            Tensor: (B, C + 3, 1, N) Grouped feature.
        
ControlNet-v1-1-nightly/annotator/uniformer/mmcv/ops/group_points.py