Delta weight sync (NCCL) produces NaN weights on Qwen3.5-122B MoE → "probability tensor contains inf/nan" crash
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 8.5k
- Forks
- 1.3k
- Avg merge
- 5h 36m
- Merged PRs (30d)
- 22
Description
Summary
With --update-weight-mode delta --update-weight-transport nccl, the first delta apply on Qwen3.5-122B-A10B (grouped MoE) leaves NaN/inf in the rollout engine's weights. The next rollout crashes in sampling. Full-sync mode (--update-weight-mode full) on the same model/config is stable. Reproduced 4/4 runs.
Symptom
TensorCompare.cu:109 _assert_async_cuda_kernel: Assertion `probability tensor contains either inf, nan or element < 0` failed
Subprocess scheduler_0 crashed with exit code -3. Triggering SIGQUIT for cleanup...
Timeline: initial full seed sync ✓ → step-1 train ✓ → step-2 delta sync applied (checksum passes) ✓ → next rollout crashes.
Config
- slime with delta sync (#1806); SGLang v0.5.13 +
docker/patch/latest/sglang.patch - Qwen3.5-122B-A10B:
--num-experts 256 --moe-grouped-gemm --moe-token-dispatcher-type alltoall --attention-backend flash(not flashinfer_trtllm) --update-weight-encoding indices, per-sync density ~1%- Reproduced on both TP2/PP2/EP16 and TP2/PP4/EP8 (parallelism-independent)
Notes
- Checksum passes, so the
(positions, values)payload arrives intact — corruption is in the apply into grouped-MoE params, not on the wire. - Possibly related: #2193 (grouped-MoE GLU rechunk expert-axis), #2104 (failed apply not surfaced) — but neither reports this crash signature.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the delta-sync apply path selected by --update-weight-mode delta and --update-weight-transport nccl, comparing it with the stable full-sync path. Reproduce on the Qwen3.5-122B-A10B grouped-MoE configuration and inspect the grouped-MoE parameter update after the checksum passes. Done means the first delta apply leaves no inf or NaN weights and the next rollout completes without the probability-tensor crash.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- distributed-systems, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Active
- Clarity
- Mostly clear
- Newbie friendliness
- 42/100