CustomOp simple abstract implementation registration (#99439)
This PR:
- adds an abstract registration API for CustomOp (CustomOp.impl_abstract)
that is used for both FakeTensor and meta tensors
- deletes CustomOp.impl_meta
The user story behind this API is that it is the one-stop shop for
registering implementations for data-less Tensors, i.e. FakeTensor and
Meta tensor.
The abstract implementation provided by the user:
- gets registered as the FakeTensor implementation AND the meta formula
- can be written like a regular meta formula. If the user decides that
they need something more special (i.e. data-dependent output shape),
then they are able to query a current context object (FakeTensorImplCtx)
that has methods to construct new unbacked symints.
Caveats:
- we really need to make FakeTensor/FakeTensorMode public. Otherwise,
there isn't a way for the user to interactively test that their abstract
implementation is correct without running through large pieces of the
PT2 stack (make_fx or torch.compile).
- We do not memoize the symints produced by
ctx.create_unbacked_symint(). It is possible to do this in the
future, but it is difficult to do soundly and I am not convinced of
the utility outside of the nonzero() usecase mentioned in #95399
Public API:
- More docs will come when we actually expose this API to users by
putting it in a public namespace, unless you folks want it now.
- The APIs mentioned in `__all__` are the ones that are intended to be
public.
Test Plan:
- Updated existing custom_op_db operators
- Added new numpy_nonzero and numpy_nms operations that test operations
that have data-dependendent output shape.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/99439
Approved by: https://github.com/ezyang
