Question about the empty_space_loss

[Net-Maker]

I am learning the scene part in this excellent work.
But I found that the empty_space_loss in paper is like that:

But in our code,it's like:

coarse_empty_space_loss = torch.zeros_like(coarse_rgb_loss)
        if self.penalize_empty_space > 0:
            depth = batch['depth'][:, None].repeat(1, _n).to(device)
            closer_mask = z_vals < (depth * self.opt.margin)
            coarse_empty_space_loss += self.empty_space_loss_fn(
                torch.tanh(torch.relu(out[closer_mask][:, 3])),
                torch.zeros_like(out[closer_mask][:, 3])
            ) * self.penalize_empty_space

I am kind of confuse. could you tell me the meaning of the double activate functions?
And where to correspond the formula in the paper?