docs: correct the enable_gqa / cuDNN explanation - #14561
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The Krea 2 PR (#14523) said no fused SDPA kernel takes a mask together with mismatched head counts and that cuDNN raises on `enable_gqa`. Neither is right: torch's cuDNN kernel accepts both, and the `enable_gqa` raises in `attention_dispatch.py` are in the context-parallel ops, not the backends. What actually happens is that torch tries its kernels in a priority order that changes across versions and GPUs, and whenever math comes before cuDNN an `enable_gqa` + mask call lands on math and materializes the full score matrix. Rewrite the GQA section of models.md around that (kernel compatibility table, why to repeat when there is a mask) and fix the Krea 2 processor comment to match. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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cc @dxqb, feel free to share feedback if you have any! |
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
sayakpaul
approved these changes
Aug 22, 2026
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