Revert "[Model Runner V2] Bug fix: logprob dtype int64/int32 issue" (#41761)#42418
Revert "[Model Runner V2] Bug fix: logprob dtype int64/int32 issue" (#41761)#42418vllm-agent wants to merge 1 commit into
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…llm-project#41761)" This reverts commit d7af6b3.
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Code Review
This pull request removes unit tests for LogprobsProcessor, deletes validation logic for logprob parameters in sampling_params.py, and refactors the GPU logprob computation kernel. Review feedback identifies a critical memory corruption risk in the Triton kernel due to an unsafe int64 cast and warns of dtype inconsistencies introduced by removing int32 casts for top-k indices. Furthermore, the removal of validation between logprobs and logprob_token_ids is flagged as a regression that could lead to inconsistent sampler behavior.
| src = per_req_token_ids_ptr + req_state_idx * per_req_token_ids_stride | ||
| valid = col < num_custom | ||
| # per_req_token_ids is int32; output is int64. | ||
| tokens = tl.load(src + col, mask=valid, other=0).to(tl.int64) |
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The explicit cast to tl.int64 before storing into out_token_ids_ptr is a potential source of memory corruption. In the V1 engine, sampled_token_ids (and consequently logprob_token_ids) are typically torch.int32. Storing a 64-bit integer into a 32-bit pointer in Triton will overwrite adjacent memory locations. Since compute_token_logprobs already handles the necessary cast to int64 for indexing at line 85, the kernel should store tokens using the native dtype of the output tensor to ensure memory safety. Note that the comment at line 205 should also be updated to reflect this change.
| tokens = tl.load(src + col, mask=valid, other=0).to(tl.int64) | |
| tokens = tl.load(src + col, mask=valid, other=0) |
| else: | ||
| # This tensor just used as an int32 pointer, data not accessed. | ||
| topk_token_ids = logprob_token_ids_state.token_ids.gpu | ||
| topk_indices = torch.topk(logits, num_logprobs, dim=-1).indices |
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Reverting the cast to int32 for topk_indices re-introduces a dtype inconsistency. In the V1 engine, token IDs are generally expected to be int32 (as seen in vllm/v1/outputs.py). By keeping topk_indices as int64 (the default for torch.topk), the resulting logprob_token_ids tensor will also be int64. This can cause issues downstream in components that expect 32-bit integers. It is safer to cast the indices to match the dtype of sampled_token_ids.
| topk_indices = torch.topk(logits, num_logprobs, dim=-1).indices | |
| topk_indices = torch.topk(logits, num_logprobs, dim=-1).indices.to(sampled_token_ids.dtype) |
| parameter="logprob_token_ids", | ||
| value=n, | ||
| ) | ||
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The removal of the validation check between logprobs and logprob_token_ids re-introduces a state where inconsistent parameters are accepted but not correctly handled by the sampler. Since the V1 sampler uses an if/else logic that prioritizes custom tokens, providing both with different lengths will lead to unexpected output formats or partially filled rows. This validation should be restored to maintain API integrity.
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Actually I don't think this PR is the reason that this test is flakey, it started after #41411. I will try to fix the test separately. |
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I also test locally pytest -q -s tests/v1/e2e/general/test_async_scheduling.py::test_without_spec_decoding
1 passed, 26 warnings in 387.00s (0:06:27)
(yewentao256) [yewentao256@nm-frk-h200-01-preserve vllm-source]$ git status
HEAD detached at d7af6b34d
nothing to commit, working tree clean
(yewentao256) [yewentao256@nm-frk-h200-01-preserve vllm-source]$ git log
commit d7af6b34d83fc691ad69347ee4d066231e5678ab (HEAD)
Author: Wentao Ye <44945378+yewentao256@users.noreply.github.com>
Date: Mon May 11 17:55:43 2026 -0400
[Model Runner V2] Bug fix: logprob dtype int64/int32 issue (#41761)Not the reason |
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Have opened #42455 which will hopefully fix it |
3 participants
Revert of #41761
Reason: This PR is suspected of causing 1 new CI failure(s) in nightly build #65755:
test_async_scheduling.py::test_without_spec_decodingfails with_all_logprobs_matchassertion error (logprobs mismatch between baseline and test configurations)PR #41761 modified
vllm/v1/worker/gpu/sample/logprob.py(logprob dtype int64/int32 fix), which is directly in the code path that produces the logprobs being compared in the failing test.Original PR: #41761
Build: https://buildkite.com/vllm/ci/builds/65755
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