Hi!
Today I found the situation when ByteTensor wrapped in Variable silently overflow, but tensor doesn’t. It’s understandable result, but shouldn’t it warn about such cases? I personally wasted two days debugging this 
>>> import torch
>>> from torch.autograd import Variable
>>> t = torch.ByteTensor([240, 240])
>>> t.sum()
480
>>> v = Variable(t)
>>> v
Variable containing:
 240
 240
[torch.ByteTensor of size 2]
>>> v.sum()
Variable containing:
 224
[torch.ByteTensor of size 1]