[export] allow register dataclass as pytree node (#106160)
In this pr, we allow users to register a customized flatten/unflatten/serialization/deserialization for a dataclass. We provide some default implementation for flatten/unflatten. We could implement a decorator based on it when needed.
## Motivation:
HuggingFace and many internal models return dataclass output and torch.export wants to maintain the invariant that export result (i.e. exported_program) has the same calling convention and result as the original callable.
This is not supported in export yet: we cannot recover the original dataclass from flattened output produced by the underlying graph module (produced by dynamo and processed further by aot_export). We need to have a place to store the metadata of the dataclass so that we can re-construct it. To avoid adding hacky code in export and allow princinpled extensibility, we think extending pytree may be a good option.
## Implementation:
@zou3519 mentioned https://github.com/pytorch/pytorch/pull/93214/files and [jax-2371](https://github.com/google/jax/issues/2371#issuecomment-805361566), which suggests that it's not a good idea to make dataclass a default pytree node but it could be good to provide a default implementation for dataclass. Since currently, this seems to be an export-only feature, we added this extension point in export.
We also add "return_none_fields" flag to control whether none fields are returned after flattening, which is expected to be False in produce_matching of dynamo.export.
Also added some tests.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/106160
Approved by: https://github.com/zhxchen17
