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Address richard's comments on libtorch_stable_abi note (#156324)

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Followups from #155984

Pull Request resolved: https://github.com/pytorch/pytorch/pull/156324
Approved by: https://github.com/zou3519
This commit is contained in:
Jane Xu
2025-06-18 08:09:27 -07:00
committed by PyTorch MergeBot
parent dcb97cd519
commit 4048a144ab
1 changed files with 3 additions and 3 deletions
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docs/source/notes/libtorch_stable_abi.md
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@ -30,16 +30,16 @@ This note will eventually contain more details on how to use the APIs in torch/c
| ? | ? | c10::SymBool | SymBool |
| ? | ? | at::QScheme | QScheme |
Our confidently supported types are the ones in the table that have completed rows. You can rely on this subset proper ABI stability.
Our confidently supported types are the ones in the table that have completed rows. You can rely on this subset for proper ABI stability.
For a limited set of use cases, we also implicitly support any literal type that is representable within 64 bits as StableIValues, as the default reinterpret_cast will succeed. These types are currently ABI-stable on best effort but might break in the future and thus should be used for short term testing only.
For a limited set of use cases, we also implicitly support any literal type that is representable within 64 bits as StableIValues, as the default reinterpret_cast will succeed. (For example: c10::Device.) These types are currently ABI-stable on best effort but might break in the future and thus should be used for short term testing only.
You can always work with StableIValue abstractions in your custom kernel for types such as c10::Device even if there is no standard defined representation of device in custom extensions by not introspecting into the StableIValue. For example, a custom operator can take as argument a StableIValue device and directly pass it through to an aten operator with `aoti_torch_call_dispatcher`.
## How to use stack-based APIs
`aoti_torch_call_dispatcher` is what we consider a stack-based API because it takes as input a stack of StableIValues. Working with the dispatcher will likely bring you into proximity with stack-based APIs, so we are documenting some invariants:
`aoti_torch_call_dispatcher` is what we consider a stack-based API because it takes as input a stack of StableIValues, which correlates with a `torch::jit::stack` of IValues. Working with the dispatcher will likely bring you into proximity with stack-based APIs, so we are documenting some invariants:
1. The stack is populated left to right.
a. For example, a stack representing arguments `arg0`, `arg1`, and `arg2` will have `arg0` at index 0, `arg1` at index 1, and `arg2` at index 2.