I have approve to split origin PRs, because origin one is too long to land.
> This description was drafted with AI assistance and reviewed by the author.
>
> This is PR 2 of 6 splitting the combined work from #193295.
>
> `BatchLinearLHSFusion.fuse()` concatenates projection weights and biases. The matcher must reject shapes that do not preserve the original linear semantics under concatenation.
>
> This PR:
>
> - rejects zero-width projection weights
> - rejects biases that are missing `example_value`, are not exactly one-dimensional, or whose width differs from the projection output width
> - groups candidates by bias presence instead of bias rank
> - adds matcher tests for valid and invalid projection shapes
> - adds end-to-end compile regressions that keep valid projections fusing while malformed projections stay eager
> - preserves zero-width eager strides in a dedicated regression
>
> **Dependency**
>
> This draft depends on PR 1. Its branch temporarily contains the earlier stack commit until that dependency merges and this PR is rebased.
>
> **Split series**
>
> 1. [[1/6] Harden batch_linear_lhs test coverage](https://github.com/pytorch/pytorch/pull/201531) (pending)
> 2. **[[2/6] Validate batch_linear_lhs projection shapes](https://github.com/pytorch/pytorch/pull/201532)** (this PR)
> 3. [[3/6] Guard batch_linear_lhs layout-sensitive users](https://github.com/pytorch/pytorch/pull/201951) (pending)
> 4. [[4/6] Add batch_linear_lhs alias regressions](https://github.com/pytorch/pytorch/pull/201533) (pending)
> 5. [[5/6] Preserve batch_linear_lhs aliases after materialization](https://github.com/pytorch/pytorch/pull/201534) (pending)
> 6. [[6/6] Re-enable batch_linear_lhs on XPU](https://github.com/pytorch/pytorch/pull/201535) (pending)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/201532
Approved by: https://github.com/jansel
Xu Han
c55d30fea6