[wip] update graph fuser aliasdb in-place (#37106)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/37106
Recomputing the aliasdb on every fusion iteration + in every subblock
is hugely expensive. Instead, update it in-place when doing fusion.
The graph fuser pass operates by pushing nodes into a fusion group. So
we start with
```
x, y = f(a, b, c)
```
and end with:
```
x_out, y_out = prim::fusionGroup(a, b, c)
x_in, y_in = f(a_in, b_in, c_in)
-> x_in, y_in
```
We destroy the `x` and `y` `Value*`s in the process. This operation is
easy to express as an update to the aliasDb--`x_out` just takes on all
the aliasing information `x` used to have. In particular, since we know
`f` and `prim::fusionGroup` are purely functional, we don't have to mess
with any write information.
This PR is the bare minimum to get this working, in the interest of
unscrewing the compilation times ASAP.
Followups I want to do:
- We don't have a way of expressing deletion of values in AliasDb. In
`graph_fuser.cpp` we sometimes construct nodes that we end up throwing
away, and we are littering `MemoryDAG` with references to dangling
pointers. Because of the way the pass works, it's fine, but this is
fragile so I want to fix it.
- We should decouple alias analysis from write tracking, to simplify the
job of keeping the write caches consistent as we mutate the aliasing
information.
- the tensorexpr fuser doesn't do this and thus is incorrect today, we
need to update it to work.
Test Plan: Imported from OSS
Differential Revision: D21219179
Pulled By: suo
fbshipit-source-id: 8ae5397b3a0ad90edec2fbc555647091f1ad5284
