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[Bugfix][Model][Rust Frontend] Qwen3_ASR: Handle ragged Qwen audio batches from Rust frontend - #60979
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…tches from Rust frontend Signed-off-by: zh98 <workallday.zhh@gmail.com>
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lesj0610
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LGTM. Both parsers pass the stacked and ragged audio tests, with padding removed per clip. Flat 2-D input still passes through unchanged.
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I tested this on an RTX 6000 Ada (sm_89) with
HTTP 200 counts:
With the PR, the concurrent passes give the same transcripts as the one-by-one pass, and both match the Python frontend: 16/16 identical in each comparison. I also logged a hash of each clip's features after unpadding. Across 8 encoder calls the input was a ragged list, e.g. Two notes for anyone reproducing:
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I've removed the unit tests as requested and pushed the changes. Thanks for the review!
Signed-off-by: zh98 <workallday.zhh@gmail.com>
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✅ Triggered Buildkite CI #94431 for commit |
…tches from Rust frontend (vllm-project#60979) Signed-off-by: zh98 <workallday.zhh@gmail.com> Co-authored-by: Isotr0py <Isotr0py@outlook.com> Signed-off-by: Andreas Karatzas <AndreasKaratzas@users.noreply.github.com>
…tches from Rust frontend (vllm-project#60979) Signed-off-by: zh98 <workallday.zhh@gmail.com> Co-authored-by: Isotr0py <Isotr0py@outlook.com>
Overview
Fixes #60970.
Fix an EngineCore crash when the Rust frontend batches Qwen3-ASR audio requests with different padded feature lengths. Normalize ragged audio features in Qwen3-ASR and the shared Qwen Omni input parser.
Claims
Test Plan / Test Result
Lint
Command
Full precommit output
Unit Test
Command:
Full pytest output
E2E Test
vllm version: 0.31.0(db9527a)
Model: Qwen/Qwen3-ASR-1.7B
Python: 3.12.14
PyTorch: 2.13.0
GPU: NVIDIA H100 80GB
CUDA graph: full and piecewise
unsqueezepath) — regression checkDetails
Root Cause
input_audio_featuresasFieldLayout::Batched, so the Rust frontend emits one item per clip — a 2-D[n_mels, padded_seq]tensor, padded to the request's longest clip.MultiModalFieldConfig.flat_from_sizes(..., dim=1): a single flat[n_mels, total_seq]tensor._reduce_datastacks only when all shapes are equal; unequal durations (or unequal intra-request padding) →return batchraw list.torch.Tensorwithdim() == 3; the list falls through and dies in TensorSchema validation.Why this is not a duplicate
Following PR (before 2026.10.10) are related but none of them solved this problem.
Pull Request Checklist
/pr-checklistskill. (Mandatory for agents, optional for humans).