Introduce quantized convolution serialization format 3 (#60241)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/60241
We're going to make a forward-incompatible change to this serialization
format soon, so I'm taking the opportunity to do a little cleanup.
- Use int for version. This was apparently not possible when V2
was introduced, but it works fine now as long as we use int64_t.
(Note that the 64-bits are only used in memory. The serializer will
use 1 byte for small non-negative ints.)
- Remove the "packed params" tensor and replace it with a list of ints.
- Replace the "transpose" field with "flags" to allow more binary flags
to be packed in.
- Unify required and optional tensors. I just made them all optional
and added an explicit assertion for the one we require.
A bit of a hack: I added an always-absent tensor to the front of the
tensor list. Without this, when passing unpacked params from Python to
the ONNX JIT pass, they type would be inferred to `List[Tensor]` if all
tensors were present, making it impossible to cast to
`std::vector<c10::optional<at:Tensor>>` without jumping through hoops.
The plan is to ship this, along with another diff that adds a flag to
indicate numerical requirements, wait a few weeks for an FC grace
period, then flip the serialization version.
Test Plan: CI. BC tests.
Reviewed By: vkuzo, dhruvbird
Differential Revision: D29349782
Pulled By: dreiss
fbshipit-source-id: cfef5d006e940ac1b8e09dc5b4c5ecf906de8716
