Why is this gt label not from the point cloud？

[Chinartist]

def get_gt_loss(self, inputs, scale, outputs, disp, depth_gt, mask):

    singel_scale_total_loss = 0

    if self.opt.volume_depth:

        if self.opt.l1_voxel != 'No':
            density_center = outputs[('density_center', 0)]
            label_true = torch.ones_like(density_center, requires_grad=False)

            all_empty = outputs[('all_empty', 0)]
            label_false = torch.zeros_like(all_empty, requires_grad=False)

            if 'l1' in self.opt.l1_voxel:
                surface_loss_true = F.l1_loss(density_center, label_true, size_average=True)
                surface_loss_false = F.l1_loss(all_empty, label_false, size_average=True)

                total_grid_loss = self.opt.empty_w * surface_loss_false + surface_loss_true

            elif 'ce' in self.opt.l1_voxel:
                label = torch.cat((label_true, label_false))
                pred = torch.cat((density_center, all_empty))

                total_grid_loss = self.criterion(pred, label)

                if self.local_rank == 0 and scale == 0:
                    print('ce loss:', total_grid_loss)

[GANWANSHUI]

this is a part of the experiment, we discuss the binary classification loss, please check the paper for details.