[https://nvbugs/6396422][fix] [nvbugs/6396422][fix] Waive AD MiniMaxM2 finegrained FP8 GSM8K numerics gap - #15840
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📝 WalkthroughWalkthroughAdds a new fine-grained FP8 TP-sharded GSM8K accuracy reference for MiniMax-M2, updates the corresponding test to pass an ChangesMiniMax-M2 FP8 Accuracy Test Un-waive
Estimated code review effort: 1 (Trivial) | ~3 minutes Possibly related PRs
Suggested reviewers: 🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
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…P-sharded path The AutoDeploy TP=4 + attn_backend=trtllm + finegrained-FP8_BLOCK_SCALES variant of TestMiniMaxM2::test_finegrained_fp8 evaluates fused QK-norm on the pre-shard flat projection (num_heads * head_dim) and applies FP8 quantization on 310 linears + 62 MoE layers. Both compound over long GSM8K outputs, dropping the measured score to ~81.2 vs the shared bf16 baseline of 89.045 (threshold 85.842), causing the test to fail. Follow the pattern used for the pytorch backend variant of the same model (cc4f2eb): differentiate the AutoDeploy FP8 + TP-sharded path via extra_acc_spec='ad_fp8_tp_attn' and register a lower reference, pass extra_acc_spec on the GSM8K evaluate call, and remove the existing waiver. Reference set to 81 (threshold 77.797) -- ~1pp below the measured 81.20 observation, giving ~3pp of headroom for run-to-run variance. This mirrors the calibration convention used in 157782c (GPT-OSS-DFlash: observed 80.895 -> reference 82.0) and e6f7d2b (GLM-4.5-Air NVFP4+MTP: 88.2 -> 70.0). A tighter margin here would risk repeat failure on the inherently noisy 1319-sample eval. Signed-off-by: trtllm-agent <296075020+trtllm-agent@users.noreply.github.com>
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Summary
MiniMaxAI/MiniMax-M2GSM8K reference ingsm8k.yamlis calibrated to the PyTorch baseline, the AutoDeploy variant fails the accuracy check and had to be waived under nvbugs/6396422.extra_acc_spec: ad_fp8_tp_attnreference entry ingsm8k.yamlset to 81 (~1pp below measured 81.20 for ~3pp headroom against run-to-run variance, following the precedent from GPT-OSS-DFlash in 157782c) and threadedextra_acc_spec="ad_fp8_tp_attn"through the test's GSM8K evaluation. This mirrors the existing pytorch analog pattern (cc4f2eb), lets the waive be removed, and avoids masking real regressions by keeping the AutoDeploy path under an accuracy gate rather than a blanket skip.Test plan
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