[Bugfix][Model Runner V2][Spec Decode] Fix off-by-one in bad_words draft-prefix matching - #52311
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…aft-prefix matching The spec-decode branch of _bad_words_kernel read draft tokens from the gathered input_ids at local position spec_offset, but local position 0 holds the last committed sampled token; draft token d_j lives at local position j + 1, as _penalties_kernel and thinking_budget's _load_effective_token already index. The shifted reads made prefix matches reaching into the draft tokens miss, fire one row late, or spuriously match by re-reading the boundary token. Signed-off-by: jyan <r_02213@sjtu.edu.cn> Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Pull request overview
Fixes a speculative-decoding-only off-by-one in the Model Runner V2 Triton _bad_words_kernel so draft-prefix matching reads the correct draft tokens (avoiding missed masks and spurious boundary matches), and adds initial GPU unit coverage for this kernel.
Changes:
- Adjust speculative branch indexing in
_bad_words_kernelby+ 1to correctly aligninput_idslocal layout for drafts. - Add a new CUDA/Triton-backed unit test suite covering committed-only, draft-only, and committed/draft-boundary bad-words prefix cases.
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.
| File | Description |
|---|---|
| vllm/v1/worker/gpu/sample/bad_words.py | Fix speculative-draft token indexing in bad-words prefix matching and document the local input_ids layout. |
| tests/v1/worker/test_gpu_bad_words.py | New GPU unit tests validating masking behavior across committed vs draft token boundaries for speculative decoding. |
Suppressed comments (1)
tests/v1/worker/test_gpu_bad_words.py:62
idx_mapping_np/expanded_idx_mappingalso hard-code the request index as 3, which couples this test toRequestState's internal slot allocation. Compute the request index from the created state and use it consistently for the mappings.
idx_mapping_np = np.array([3], dtype=np.intp)
expanded_idx_mapping = torch.tensor(
[3] * num_logits, dtype=torch.int32, device=DEVICE
)
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Signed-off-by: jyan <r_02213@sjtu.edu.cn> Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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✅ @jyan-R, CI is now available for this PR.
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#14433) ### What this PR does / why we need it? 同步上游更改 vllm-project/vllm#52311 ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? - vLLM version: v0.27.1 - vLLM main: vllm-project/vllm@58d3918 Signed-off-by: liyishi <1252651434@qq.com>
vllm-project#14433) ### What this PR does / why we need it? 同步上游更改 vllm-project/vllm#52311 ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? - vLLM version: v0.27.1 - vLLM main: vllm-project/vllm@58d3918 Signed-off-by: liyishi <1252651434@qq.com>
…t token offset in bad words kernel (from #14433) (#14526) Cherry-pick of PR #14433 onto `releases/v0.26.0rc`. Original PR: #14433 Original author: @SOMEONEUNSEEN --- ### What this PR does / why we need it? 同步上游更改 vllm-project/vllm#52311 ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? - vLLM version: v0.26.0 - vLLM main: vllm-project/vllm@d02df74 Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
…aft-prefix matching (vllm-project#52311) Signed-off-by: jyan <r_02213@sjtu.edu.cn> Co-authored-by: jyan <r_02213@sjtu.edu.cn> Co-authored-by: Claude Fable 5 <noreply@anthropic.com> Co-authored-by: mergify[bot] <37929162+mergify[bot]@users.noreply.github.com> Signed-off-by: Zhu, Zufang <zufang.zhu@intel.com>
vllm-project#14433) ### What this PR does / why we need it? 同步上游更改 vllm-project/vllm#52311 ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? - vLLM version: v0.27.1 - vLLM main: vllm-project/vllm@58d3918 Signed-off-by: liyishi <1252651434@qq.com>
…t token offset in bad words kernel (from vllm-project#14433) (vllm-project#14526) Cherry-pick of PR vllm-project#14433 onto `releases/v0.26.0rc`. Original PR: vllm-project#14433 Original author: @SOMEONEUNSEEN --- ### What this PR does / why we need it? 同步上游更改 vllm-project/vllm#52311 ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? - vLLM version: v0.26.0 - vLLM main: vllm-project/vllm@d02df74 Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Purpose
Fix an off-by-one in the spec-decode branch of
_bad_words_kernel(vllm/v1/worker/gpu/sample/bad_words.py), present since the kernel was introduced in #33433.The sampler passes
input_idsgathered atlogits_indices, so for a spec-decode request the per-request local layout is: local position 0 = last committed sampled token, local position j = draft token d_{j-1}. The sibling kernels index draft tokens accordingly (_penalties_kernelusesstart_idx + prev_pos + 1; thinking budget's_load_effective_tokenuses+ 1with an explicit comment)._bad_words_kernelreadinput_ids_ptr + cur_req_first_pos + spec_offsetwithout the+ 1, so every draft-region read was shifted back by one token (the boundary token was read twice).Consequences when bad_words and speculative decoding are combined and a multi-token bad word's prefix window reaches into the draft tokens:
Single-token bad words and non-spec rows are unaffected. Model Runner V1 has a separate implementation and is unaffected.
Not a duplicate: searched open PRs/issues for
bad_words+ spec decode / off-by-one /_bad_words_kernel; no existing fix found (closest is #34213, which only touches penalties).Test Plan
New unit test (first coverage for this kernel), following the pattern of
tests/v1/worker/test_gpu_thinking_budget.py:Scenario: committed output
[10, 11], draft tokens[12, 13]. The core regression case is the boundary-spanning prefix ([11, 12, 30]must mask at the row where the prefix completes, not one row later); the other three cases pin the remaining coverage axes: a positive match at draft offset >= 1 ([12, 13, 40]), a no-double-count guard for the boundary token ([11, 11, 50]), and a committed-only baseline ([10, 11, 60]). Assertions compare the full logits tensor.Test Result
Ran on an A100 SXM4 80GB (torch 2.13.0+cu130, triton 3.7.1, Python 3.11), with the branch installed editable via
VLLM_USE_PRECOMPILED(nightly x86_64 wheel66728feb1):4 passed.bad_words.pyswapped in):3 failed, 1 passed— exactly the three spec-branch cases fail; the committed-only baseline passes.ruff check/ruff format --checkpass on both changed files.+ 1the kernel matches the reference in all cases, without it ~24% of scenarios diverge.AI assistance was used for this change (Claude); I have reviewed every changed line.