I can tell pytorch 1.10 doing this is for performance and memory saving. But for a user, especially engineer, we will not expect this behavior. Changing the z wil lead to x change, so I need a lot of “.clone()” to void math calculation wrong. This will not speed up anything… Both coding and performance are even slower.
Also, does the numpy people know .conj() using share memory will be faster? Of course, they know. But why didn’t they do it? Because it is anti-math, people using complex number heavily depend on math. If it is too different from math way, it is really hard for the user…
That is my a opinion. Maybe, I am wrong, but please think about it. Thanks.