def METHOD_NAME(self, points, calibs, transforms=None, labels=None):
    if labels is not None:
        self.labels = labels
    xyz = self.projection(points, calibs, transforms)
    xy = xyz[:, :2, :]
    xyz_feat = self.depth(xyz)
    self.intermediate_preds_list = []
    im_feat_256 = self.im_feat_list[0]
    im_feat_512 = self.im_feat_list[1]
    point_local_feat_list = [
        self.index(im_feat_256, xy),
        self.index(im_feat_512, xy), xyz_feat
    ]
    point_local_feat = torch.cat(point_local_feat_list, 1)
    pred, phi = self.head(point_local_feat)
    self.intermediate_preds_list.append(pred)
    self.phi = phi
    self.preds = self.intermediate_preds_list[-1]