Solved by Nikronic in post #2 
              
              
                Hi, 
Actually, this is not a skipped bug or something like that. Numpy also has same semantic and it is due to precision of floating point numbers. 
 

You can find some information about dtypes wrt to this post by using 
i = torch.finfo(torch.float32)
i.eps  

Bests