Hello!

I have noticed that, even though I am actively fixing the seed, there are small differences between runs when the I multiply two tensors. More specifically, I have located a run in which I perform an element wise multiplication of two tensors and, in one run, the multiplication of `torch.sigmoid(torch.tensor(0.0000))*torch.sigmoid(torch.tensor(0.1744))`

returns `0.2717`

and other in which returns `0.2718`

. I am highly confused and I don’t really know how can I fix it. It’s important since this small differences accumulated and provoke higher differences in the long term. I set the same seed in both experiments and both run in the same GPU model.

I have investigated more the issue and apparently the difference is not in the multiplication but in the output of a loss function, the difference is quite small and cannot be captured with the precision of the print I wrote, but in some cases I get `0.0053490624`

vs `0.0053490633`

. Could this be fixed simply changing the data type?

Thanks!