fused-kernel
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problem 118 tok
When replacing a full SDPO loss function with a memory-efficient fused JSD kernel for distillation training, the importance sampling ratio correction for off-policy steps gets silently dropped. The fused kernel computes JSD only and returns a scalar loss. With steps_per_batch > 1, steps 2+ train on…
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problem 781 tok
Fused-kernel rewrites of CLaaS-style SDPO distillation (e.g. swapping compute_sdpo_loss(...) for a torch.autograd.Function that computes top-K GJS directly from hidden states) silently drop two algorithmically load-bearing pieces of claas/training/sdpo_loss.py : IS-ratio clipping for off-policy…
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