[Bugfix][Model] Fix CohereASR streaming audio-token estimate (unit + subsampling)

[hungnnvidia]

Summary

CohereAsrForConditionalGeneration.get_num_audio_tokens(audio_duration_s, stt_config, model_config) — the duration-based estimate used to add audio tokens to prompt_tokens for streaming transcription usage stats — had two bugs in one small classmethod:

1. Unit mismatch. It used preprocessor["window_stride"] (a stride in seconds, ~0.01) directly as the divisor of audio_duration_s * sample_rate (a sample count). The feature extractor's hop is int(window_stride * sample_rate) samples (see get_hf_processor), so this divided by 0.01 instead of 160.
2. Missing subsampling. It never divided by the encoder subsampling_factor, unlike the per-request path CohereASRProcessingInfo.get_num_audio_tokens (get_seq_len(...) then ceil(.../ subsampling_factor)).

Together these inflated the reported prompt_tokens by ~5 orders of magnitude.

Root cause

vllm/model_executor/models/cohere_asr.py  (classmethod get_num_audio_tokens)
    hop_length = window_stride              # seconds (~0.01), not samples
    ceil(duration * sample_rate / hop_length)   # + no /subsampling_factor

Reached from vllm/entrypoints/speech_to_text/base/serving.py where the return value is added to num_prompt_tokens for streaming usage.

Reproduction (before fix)

Calling the real classmethod with a realistic config (window_stride=0.01, sample_rate=16000, subsampling_factor=8):

duration=  1.0s  classmethod=   1,600,000  expected≈  13  ratio=123,077x
duration= 10.0s  classmethod=  16,000,000  expected≈ 125  ratio=128,000x
duration= 30.0s  classmethod=  48,000,000  expected≈ 375  ratio=128,000x

After fix

duration=  1.0s  classmethod=          13  expected≈  13  ratio=1x
duration= 10.0s  classmethod=         125  expected≈ 125  ratio=1x
duration= 30.0s  classmethod=         375  expected≈ 375  ratio=1x

Fix

Convert window_stride to a sample hop and divide by the encoder subsampling factor, mirroring the per-request get_seq_len path.

Tests

.venv/bin/python -m pytest tests/models/multimodal/test_cohere_asr_audio_tokens.py -v
# 1 passed

Linters:

pre-commit run ruff-check  --files ...  # Passed
pre-commit run ruff-format --files ...  # Passed
pre-commit run mypy-3.12   --files ... --hook-stage manual  # Passed

Not a duplicate

No open/closed PR touches get_num_audio_tokens in cohere_asr.py (the only open cohere_asr PR, #39259, is about a librosa import). Verified via gh pr list --search.

AI assistance was used to prepare this change.

[claude]

Claude Code Review

This pull request is from a fork — automated review is disabled. A repository maintainer can comment @claude review to run a one-time review.

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[hungnnvidia]

@claude review

[github-actions]

❌ @hungnnvidia, A reviewer with write access must run /ci run, approve the PR, or add the ready label first.

[aaron-seq]

Hello @hungnnvidia, Checked the arithmetic against get_seq_len and the reported numbers hold for durations that are exact multiples of the hop. Two things I would want settled first. The estimate uses ceil where get_seq_len floors, so it runs one token high on roughly 11% of durations, and the test derives its expected value from the same formula it is testing, so it cannot catch that. Everything else reads right to me, and the description already covers disclosure and the duplicate check. Someone with write access will need to kick off /ci run since this touches a serving path.

[hungnnvidia]

Thanks @aaron-seq, all good catches — I pushed an update:

• ceil vs floor: switched the frame count to // hop_length so it matches get_seq_len's floor_divide (with exact_pad off by default). That removes the ~11% one-token-high cases.
• sample_rate: now read from preprocessor["sample_rate"] (same key as get_hf_processor) instead of stt_config.sample_rate.
• assert → default: window_stride now uses .get("window_stride", 0.01), matching get_hf_processor and surviving python -O.
• subsampling_factor: left as encoder["subsampling_factor"] on purpose — the per-request path (CohereASRProcessingInfo.get_num_audio_tokens) indexes it the same way and also raises KeyError, and it's a hard-required encoder field (ConformerEncoder asserts subsampling_factor > 1). Defaulting it to 1 would silently 8× the estimate on a malformed config, which seemed worse than a loud error — but happy to switch to .get(..., 1) if you'd prefer strict symmetry.
• test: now asserts the concrete 13 / 125 / 375 values instead of re-deriving them from the formula under test.

Let me know if you'd like the subsampling_factor symmetry change too. This will need a maintainer to /ci run since it touches the serving path.

[hungnnvidia]

Thanks for the review @aaron-seq — I pushed an update addressing all points. This is reproduction when rerunning against the new code:

Updated classmethod (floor frames, /subsampling_factor):
  duration=  1.0s  ->  13 tokens
  duration= 10.0s  ->  125 tokens
  duration= 30.0s  ->  375 tokens
ceil vs floor agreement check (non-multiple-of-hop durations):
  duration= 6.401s  code= 80  floor= 80  ceil= 81  MATCHES floor
  duration=12.801s  code=160  floor=160  ceil=161  MATCHES floor
  duration= 0.081s  code=  1  floor=  1  ceil=  2  MATCHES floor
  duration=  7.37s  code= 93  floor= 93  ceil= 93  MATCHES floor

[aaron-seq]

Changes look right to me. Flooring matches get_seq_len, and reading both sample_rate and window_stride from preprocessor lines this up with get_hf_processor. The non multiple of hop numbers you ran are exactly the check I wanted to see.

On subsampling_factor, agreed, leave it as is. A loud KeyError beats silently multiplying the estimate by 8, and it matches the per request path. Not worth changing.

The pre-commit failure is not yours. pre-run-check needs the verified, ready, or ready-run-all-tests label before it will run, so a maintainer has to apply one. Same person can kick off /ci run after that.

[hungnnvidia]

@DarkLight1337 could you help me review this PR

[hungnnvidia]

Thanks @aaron-seq, appreciate the thorough review. Glad the floor/get_seq_len alignment and the non-multiple-of-hop numbers check out, and agreed on leaving subsampling_factor as a hard KeyError for parity with the per-request path — no further changes planned on my side.

Understood on the pre-run-check gate; the PR is ready whenever a maintainer can apply the label and kick off /ci run.

[hungnnvidia]

@DarkLight1337 I saw you verified this PR, could you help me merge it

[DarkLight1337]

Cohere folks said they will take a look at this PR

[ekagra-ranjan]

@hungnnvidia - Thanks for the bugfix and adding a test! Left a small comment and LGTM otherwise

[ekagra-ranjan]

LGTM!

[DarkLight1337]

/ci run

[github-actions]

✅ Triggered Buildkite CI #86848 for commit fe2e6e437092.