implementation of the loss function from paper

[Irrelifant]

Hey everyone,

first of all, thanks for your implementation
the following formula from the paper "Auxiliary Tasks in Multi-task Learning"

was implemented by:

        loss_sum += 0.5 / (self.params[i] ** 2) * loss + torch.log(1 + self.params[i] ** 2)

but imo this is not exactly true, since 0.5 / sigma^2 is not the same as 1/(2*sigma^2) am I right or do i oversee something here?

Thanks for feedback

[ress4859]

1/(2*sigma^2)= 1/2 (1/sigma^2)=0.5(1/sigma^2) = 0.5/(sigma^2)