Switch to pybind11 style registration function API. (#36258)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/36258
Previous we had a && chaining style API. There are some downsides to
this API:
- It's easy to forget the 'static' qualifier in front, leading to
subtle ODR bugs.
- It is not compatible with torchbind class_ definitions, as these
need multiple levels of chaining. So in practice people end
up having to define multiple static initializers, one per class.
- It's not like pybind11.
- There's no way to conveniently get the file and line number of
the registration, as there is no macro point in the API.
- The old API doesn't really encourage people to put all of their
definitions for a library in one place, and to give a custom
namespace for it. Similarly, the old API wasn't very DRY, because
you had to keep repeating the namespace/dispatch key you
were writing implementations for.
The new API is modeled exactly off of the PYBIND11_MODULE macro:
you write:
```
TORCH_LIBRARY(aten, m) {
m.def("aten::add(Tensor self, Tensor other) -> Tensor");
...
}
```
in a non-chaining fashion, and under the hood the macro expands to
define a function, and define a static initializer that allocates
c10::Library (previously called c10::Module, but we renamed it
to avoid confusion with the existing NN module concept), passes
it to your function, and then retains it for the rest of the lifetime
of the program. Specification of the namespace is mandatory,
and in later commit I plan to make it a hard error to TORCH_LIBRARY
the same library name twice.
If you are specifying an implementation for an existing operator
(e.g., you're the XLA backend, or even if you're just putting
registrations for implementations at the implementation site),
you should use TORCH_LIBRARY_IMPL, which instead takes a backend
argument (instead of namespace) and can be used to specify an
implementation for a backend. Unlike TORCH_LIBRARY, you can do
as many of these as you want for a backend.
This needs updates to the mobile code analyzer.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Test Plan: Imported from OSS
Differential Revision: D20929257
Pulled By: ezyang
fbshipit-source-id: ba04d78492e8c93ae7190165fb936f6872896ada