[V1][SpecDecode] Resume relaxed acceptance for thinking-mode tokens (port of #22238)#43184
[V1][SpecDecode] Resume relaxed acceptance for thinking-mode tokens (port of #22238)#43184chaeminlim-mb wants to merge 1 commit into
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…tio variant) Continuation of vllm-project#22238 (DW934/NVIDIA), which auto-closed on 2025-12-10 after the original author went silent post-WoosukKwon's "who needs this" question. Ports the ratio variant onto current main and adds a fix for the gemini-flagged thinking_states OOB blocker. Behavior: * Default OFF (relaxed_thinking=False). Identical to pre-patch when the new SpeculativeConfig fields are unset. * When enabled, applies only during thinking phase (between <think>/</think> token IDs from reasoning_parser). Outside the thinking phase, falls back to strict greedy. * Acceptance rule (greedy path only): P(draft_id) >= P(top-1) * relax_ratio AND draft_id in target's top-K. * Random sampling path unchanged (same scope as vllm-project#22238). Adds 4 SpeculativeConfig fields: relaxed_thinking: bool = False relax_ratio: float = 1.0 (1.0 == no relaxation) relax_top_k: int = 1 (1 == greedy/strict equivalent) reasoning_parser: str | None = None New Triton kernel `relaxed_thinking_sample_kernel` lives next to the existing rejection sampler; gated by use_relaxed = relaxed_thinking AND thinking_states is not None AND .numel() == batch_size. Also fixes the thinking_states-empty OOB blocker that gemini-code-assist called out on vllm-project#22238 (`_make_cached_request_data` now populates the states explicitly instead of leaving the list empty when the kernel expects per-batch entries). References: vllm-project#22238 (NVIDIA, V1 attempt — closed by stale bot) vllm-project#21506 (NVIDIA, V1 attempt — closed by stale bot) sgl-project/sglang#7702 (pyc96 — still open) sgl-project/sglang#8068 (pyc96 — still open) Co-authored-by: Jaeyoun Kim <jaeyoun.kim@mangoboost.io> Signed-off-by: Chaemin Lim <chaemin.lim@mangoboost.io>
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Code Review
This pull request implements a "relaxed acceptance" mechanism for speculative decoding during a model's thinking phase, ported from vLLM PR #22238. It introduces configuration options to enable this feature, tracks the thinking state of individual requests based on token boundaries (e.g., and ), and adds a specialized Triton kernel to handle relaxed greedy rejection sampling. The reviewer suggests adding validation for the relax_top_k parameter to ensure it is positive and to prevent potential performance issues or crashes from excessively large values.
| if getattr(speculative_config, "relaxed_thinking", False): | ||
| self.relaxed_thinking = True | ||
| relax_ratio = speculative_config.relax_ratio | ||
| relax_top_k = speculative_config.relax_top_k |
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The value of relax_top_k is used directly in torch.topk and as a constexpr in a Triton kernel. A non-positive or very large value could cause crashes or significant performance issues (e.g., OOM, kernel recompilation/slowness). It's recommended to add validation for relax_top_k.
At a minimum, relax_top_k should be positive. You might also consider adding a reasonable upper bound (e.g., 16 or 32) and logging a warning if it's unusually large, to prevent accidental misconfiguration.
Example validation:
if not relax_top_k > 0:
raise ValueError(
f"relax_top_k must be positive, but got {relax_top_k}"
)
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@chaeminlim-mb Thank you very much for your contribution! I’m terribly sorry that I haven’t had time to continue the work I started recently, so I’d be very grateful to anyone who could pick up where I left off. Looking forward to seeing further work on this PR! |
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This pull request has merge conflicts that must be resolved before it can be |
2 participants
Purpose
This PR is a continuation of #22238 and #21506, both of which closed
via the stale bot in December 2025 without merge. The feature: during
reasoning models' thinking phase (tokens between
<think>and</think>as identified byreasoning_parser), use a relaxedgreedy acceptance rule for speculative decoding:
Outside the thinking phase, falls back to the standard strict-greedy
acceptance. Random-sampling path is unchanged (same scope as #22238).
The original PR's only stated concern from a maintainer was "what is
this feature mainly for, and who will be using this?" — we attempt
to answer that directly below.
Who would use this
DeepSeek-R1 / QwQ / similar reasoning-tuned models where the
thinking phase is the dominant portion of the output (we measured ~85%
of output tokens lying inside
<think>…</think>on DeepSeek-R1-0528gsm8k samples) and where users are willing to trade a bounded amount
of strict accuracy for higher acceptance-length / throughput. The
feature is opt-in (default OFF), so deployments that need strict
accuracy guarantees are not affected.
Smoke data on a single gfx942 node (DeepSeek-R1-0528, no PD, c=30,
100 gsm8k samples):
This is one data point; a larger sweep across
r × kat 500 samplesis in progress and will replace this row before the PR is flipped to
ready. If the sweep doesn't show a usable region, the PR will be
revised or closed.
Changes
7 files, +288 / -16 lines. Mirrors #22238's file scope; the only
differences are (a)
vllm/config/speculative.pyinstead ofvllm/config/__init__.py(the config module was split since #22238was filed), and (b) the OOB fix below.
vllm/config/speculative.py: add fourSpeculativeConfigfields with safe defaults:
vllm/v1/sample/rejection_sampler.py: new Triton kernelrelaxed_thinking_sample_kernel; the sampler's main path now readsthe four config fields plus a
thinking_statestensor (per-requestin-thinking-phase bool) and gates the relaxed branch on
use_relaxed = relaxed_thinking AND thinking_states is not None AND thinking_states.numel() == batch_size.vllm/v1/core/sched/scheduler.py+output.py+utils.py+request.py: track whether each request iscurrently inside a
<think>block based onreasoning_parser-provided start/end token IDs, and forward thebit through
CachedRequestDatato the worker.vllm/v1/worker/gpu_model_runner.py: assemble the per-batchthinking_statestensor and pass it into the sampler.The signal is currently batch-level (one bool per request, applied
uniformly across that request's draft tokens in the verify step). A
per-token mask would let mid-batch transitions through the thinking
boundary be sampled more precisely; we went with the batch-level
form because it mirrors the design in #22238, but the kernel is
straightforward to extend if reviewers prefer per-token granularity.
Fix on top of #22238
#22238's automated review flagged a critical bug: in some branches
_make_cached_request_dataleftthinking_statesempty, and thekernel — which expects one entry per batch row — read out-of-bounds.
This port populates the state explicitly in every branch, and the
sampler short-circuits (
use_relaxed = False) if the tensor's sizedoesn't match the batch, eliminating the OOB path.
Backward compatibility
SpeculativeConfigfields default to values that produceidentical behavior to pre-patch (
relaxed_thinking=Falseskips theentire relaxed path;
relax_ratio=1.0+relax_top_k=1wouldreduce to strict greedy even if the flag were on).
kernel is a new entry point, not a modification of the strict one.
Not a duplicate of
re-port onto current main + the OOB fix above. Closed by stale bot.
same fate.
filed.
distinct knob; threshold is a scalar applied to all tokens
regardless of thinking phase.
bounds the number of thinking tokens; orthogonal to acceptance.
debugging hook for testing rejection sampling; not a production
knob.
SGLang's parallel effort (sgl-project/sglang#7702 and #8068) is
still open; if there's interest, the two stacks could share a
config schema.
Searched on 2026-05-19 for
relaxed acceptance,draft acceptance,thinking speculative,relax_ratio,deepseek_v3_relaxed,relax_top_k— nothing else is actively driving this in vLLM.Verification status
pre-commit run --files <all 7 changed files>— passes (ruffcheck, ruff format, mypy-3.10, SPDX, lazy-imports, forbidden-imports,
attention-backend docs, etc.).
mainis clean (0 conflicts).cluster repro (AMD MI300X, DeepSeek-R1-0528, 1P1D) will be added
with the sweep results.
AI assistance disclosure
Drafted with AI assistance (Claude Code). I (chaemin.lim@mangoboost.io)
am the human submitter, have reviewed each changed line, and will
defend the change through review. The code itself is a direct port of
#22238 plus the OOB fix described above; the port was prepared by my
colleague (
Co-authored-bytrailer in the commit) and is beingsubmitted under my account because I'm carrying the upstream
conversation across our team's MoRI-IO PRs (#43063, #43065, #43067,
#43068).