Bug: dividing speed_loss by batch size twice
dHonerkamp opened this issue · comments
In the file coiltraine/network/loss.py
we find the following lines from 56 onwards:
loss_function = loss_branches_vec[0] + loss_branches_vec[1] + loss_branches_vec[2] + \
loss_branches_vec[3]
speed_loss = loss_branches_vec[4]/(params['branches'][0].shape[0])
return torch.sum(loss_function) / (params['branches'][0].shape[0])\
+ torch.sum(speed_loss) / (params['branches'][0].shape[0]),\
It seems the speed_loss is being divided by params['branches'][0].shape[0]
(the batch_size?) twice instead of only once. While the rest of the loss ('loss_function') is not.
Is this indeed a bug that changes the scaling of the different losses or am I missing something?
I confuse about this points. I also want to know.
Yes, I found this recently. It was dividing twice.
Thanks for pointing this out. I wouldnt' change that on the repository since this is necessary
in order to reproduce the results.
This shows that the speed prediction should probably use a way smaller
weight than what i used originally.