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Use cuDNN's deterministic dprob in the fused grouped MLP
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[Common] Default EP comm kernels to 32 SMs; keep shuffle/preprocess on all SMs
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fix: guard backward_dw() bias-grad backfill against a legitimately-empty bgrad
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Thread tanh logit softcapping through FlashAttention (FA2, opt-in FA3)
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[JAX] Return max_logit from TE fused attn
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Fix: fused QUproj + RoPE + Quant
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[PyTorch] Reduce CPU overhead on eager EP dispatch and combine
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[All] Refactor fused attention APIs with cuDNN-frontend support checks and opaque config/params handles
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