[Bugfix] Correct block shape logic in WNA16 MoE triton kernel#31686
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JartX wants to merge 2 commits intovllm-project:mainfrom
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[Bugfix] Correct block shape logic in WNA16 MoE triton kernel#31686JartX wants to merge 2 commits intovllm-project:mainfrom
JartX wants to merge 2 commits intovllm-project:mainfrom
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Signed-off-by: JartX <sagformas@epdcenter.es>
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This pull request introduces a bugfix for the WNA16 MoE Triton kernel by correcting the block shape logic. It ensures that BLOCK_SIZE_N and BLOCK_SIZE_K are always set in the configuration before the kernel grid is defined, which resolves an inference regression. Additionally, the code is refactored to use a new dispatch_fused_moe_kernel function, which adds support for zero-point quantization (w1_zp and w2_zp) for the expert weights. The changes appear correct and improve the robustness and functionality of the fused MoE layer.
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#31752 works fine close it |
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This PR addresses an inference regression introduced in PR #31050. Specifically, it fixes a failure when loading models that use WNA16 Triton.
Note: This PR depends on PR #31663, which contains the fix for the failure introduced in PR #31533.
CC: @zyongye @robertgshaw2-redhat @jeejeelee — please take a look. :)