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Documentation preview: https://vllm--65326.org.readthedocs.build/en/65326/ |
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Tested end-to-end on WSL2 with an NVIDIA GeForce RTX 5060 Laptop GPU. Environment Details Verification Details Test Target: tests/v1/engine/test_async_llm.py::test_queued_request_waits_for_reload_after_level2_sleep Model: Qwen/Qwen3-0.6B Execution Command: VLLM_USE_FLASHINFER_SAMPLER=0 pytest -v -s tests/v1/engine/test_async_llm.py::test_queued_request_waits_for_reload_after_level2_sleep
Tested against the base commit. The queued request was scheduled immediately after memory allocation and evaluated against uninitialized/discarded memory (zeroed out weights), leading to repeated ! tokens under greedy decoding:
Ran the test on the PR HEAD. Scheduling was held after the tagless wake, and unpaused only after reload_weights() finished: Confirmed that: The first tagless wake_up() detected incomplete weights, kept the scheduler paused (PAUSED_NEW), and logged the warning as designed. The scheduler transitioned to UNPAUSED only after weight reload. The output of the queued request matched the expected inference result before sleep without generating gibberish. LGTM! |
| "scheduling stays paused. Reload them, then call wake_up again, " | ||
| "or wake_up(tags=['scheduling']) if they were restored otherwise." | ||
| ) | ||
| return False |
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This looks like it breaks test_release_kv_cache_memory_preserves_generation[sleep-2] in test_cumem.py: it does wake_up(), then reload_weights, then asserts not is_sleeping(), and with this return the scheduler's still PAUSED_NEW at that point. I ran that sequence on CPU against the real EngineCore, Scheduler and Worker methods with the memory backend stubbed, and a queued request never got scheduled after the reload, even over 1000 schedule() calls. The steps in #65325 hit the same thing, so that queued curl now hangs instead of returning garbage, and the only sign is a warning in the server log. Could the engine resume once reload_weights clears the flag when a tagless wake is being held, so the old order keeps working?
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Hi Paolo, thanks, you’re right: holding the wake broke the documented wake_up() → reload_weights order and turned wrong output into a hang. I compared a few approaches and decided to only act on requests that are certain to run on discarded weights, rather than have the engine guess when the weights are valid.
the New approach: a wake that remaps the discarded weights and resumes scheduling in one call fails the queued requests with a retryable 503; every other order, including test_cumem, is unchanged.
…resumes before the weights are restored A wake_up that remaps the weights discarded by level-2 sleep and resumes scheduling in the same call, such as a tagless wake, leaves no point to restore them first, so the next step ran every queued request on the discarded weights and returned it with HTTP 200. Such a wake now finishes those requests with a retryable error (weights_not_restored, HTTP 503) before resuming. Every other wake order, level-1 sleep and checkpoint restore are unchanged, and nothing waits on a weight-restore signal. Signed-off-by: Hang Zhengyang <hang.zhengyang1010@gmail.com> Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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| def _fail_requests_on_discarded_weights(self) -> list[Request]: | ||
| failed = self.scheduler.finish_requests(None, RequestStatus.FINISHED_ERROR) |
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With multiprocessing disabled, a request queued during level-2 sleep is removed here without sending a final result back to the caller. It still looks unfinished, so the caller can keep looping on empty results. Please send the error back on that path too and add a regression test.
Overview
After level-2 sleep, a
wake_up()that remaps the discarded weights and resumes scheduling in the same call (e.g. a tagless wake) ran every request queued during sleep on the discarded weights and returned it with HTTP 200. Such a wake now fails those requests with a retryable error (HTTP 503) instead. Fixes #65325 (duplicate: #65324).Claims
RequestError(code="weights_not_restored", retryable=True)before resuming, so none of them reaches the model. The server returns 503, as it does forengine_paused.weights, restore,kv_cache), withreload_weights, a weight update or a custom loader; a tagless wake with nothing queued, thenreload_weights(the documented order,test_cumemsleep-2); level-1 sleep; checkpoint restore.wake_up's return value andis_sleepingare unchanged, nothing waits on a weight-restore signal, and no API is added.docs/features/sleep_mode.mdand the warning point deployments that receive requests while asleep to the staged wake.Validation
Reproduction from #65325 against
vllm serve Qwen/Qwen3-0.6B --enable-sleep-mode(greedy, 32 tokens):wake_up, thenreload_weights!!!!!!!!…weights_not_restored, warning loggedreload_weightsweights,reload_weights,kv_cacheTests (
VLLM_USE_FLASHINFER_SAMPLER=0only because the test host has no CUDA toolkit for the FlashInfer sampler JIT), on this branch rebased onto main 30cff7b:test_level2_wake_fails_requests_queued_before_reload(realAsyncLLM, Qwen/Qwen3-0.6B): a request queued during level-2 sleep fails withRetryableRequestErroron a tagless wake and the next request afterreload_weightsmatches the pre-sleep output; under a staged wake and under level-1 sleep the queued request matches it.test_wake_up_fails_requests_on_discarded_weights(CPU, realExecutorsleep/wake bookkeeping): tagless,["weights", "kv_cache"]and kv-first-then-weights wakes fail the queued requests before resuming; staged, level-1, level-2-on-level-1 and level-1-after-a-staged-level-2 wakes do not.tests/v1/worker/test_sleep_mode_backend.pypassed (9), andtests/model_executor/test_sleep_mode_tensor_ownership.pyandtests/entrypoints/rl/state_transitions/test_sleep.pypassed except cases that need gated or audio-only models on the host.test_engine_core_tpfails identically on main on this host.pre-commit runon the changed files passes, including mypy.Details
Root cause.
EngineCore.wake_upresumes scheduling once all executor memory is resident. Level-2 sleep discards the weights (SleepModeBackend.suspend), so memory being resident does not mean the weights are valid. When one call remaps the weights and resumes, the caller cannot restore them in between: the next engine step runs before anyreload_weightsRPC arrives, which is why #65325 reproduced 10 of 10 times.Fix.
EngineCorerecords that level-2 sleep discarded the weights (only when the executor actually slept; a level-2 sleep on top of level 1 is a no-op there) and clears it on the first wake that remaps them. If that wake also resumes scheduling, the queued requests would deterministically run on discarded weights, so they are finished first, with the same retryable error pathpause_generationuses forengine_paused. The check only reads executor state after a level-2 discard.Why fail instead of holding scheduling until the reload. The previous revision of this PR held a tagless wake until another
wake_upafter the reload. As pointed out in review, that broke the documentedwake_up()thenreload_weightsorder (test_cumemsleep-2) and turned the wrong output into a hang. Holding scheduling and resuming it automatically once the weights are restored (the approach in #65668) keeps that order working, but needs the engine to know when the weights are valid: a weight update throughfinish_weight_updateor a custom loader passed tocollective_rpcrestores them without a signal the engine can rely on, so such engines would stay paused, including under the staged wake. This revision only acts on requests whose output was certain to be wrong, so no previously correct sequence changes behavior.Related: #48310 (RL sleep/wake correctness RFC; its canonical transition is the staged wake), #65668, #64184, #29341.
Pull Request Checklist
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