fix: survive GPU re-provisioning and stale scan caches - #14
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Three failure modes from the 2026-08-31 incident, where the VM was re-provisioned from two 15 GB vGPUs (31 GB RAM) to one 24 GB L4-24Q (28 GB): 1. Workers configured for the removed GPU failed CUDA init and silently fell back to CPU inference. large-v3 on CPU loads ~6 GB of weights into host RAM per worker and runs orders of magnitude slower; two such workers pushed RSS to 29 GB and the kernel OOM-killed the service every ~40 minutes. Remove the fallback: raise a clear error instead. --no-cuda still selects CPU deliberately. 2. Nothing checked configured GPU indices against reality. init_gpu_assigner now drops indices that exceed the visible CUDA device count with a warning, degrading to fewer GPUs; if none remain it raises, and run() exits 2 with the message instead of a traceback. Enumeration failure fails open -- a false negative would disable GPUs that work. 3. The scan cache was trusted forever. A cache written on 2026-01-23 was loaded verbatim for seven months, hiding ~1,200 newly added videos behind "0 transcriptions, 0 translations needed" every cycle. Caches older than --scan-cache-max-age-hours (default 24, 0 disables) are ignored and rebuilt by the normal scan path. The run script also gains a TRANSCRIBE_MINUTES_BUDGET passthrough, defaulting to 150 for this host: the tool's 220 default was sized against the 31 GB this box had before the re-provision cut it to 28 GB. All three fixes verified non-vacuous: reverting each makes its tests fail (4 failures across the 7 new tests), restoring makes all 65 pass.
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🟡 Changes recommended
Two edge cases introduce incorrect runtime behavior in long-running use (stale gpu_assigner global across cycles; unvalidated negative/NaN/inf --scan-cache-max-age-hours).
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Pull request overview
This PR hardens archive_transcriber against GPU re-provisioning and stale scan-cache behavior that caused silent CPU fallback/OOM loops and missed newly added videos.
Changes:
- Remove CUDA→CPU fallback on CUDA init failure; raise a clear error instead.
- Validate configured
--gpusindices against visible CUDA device count, dropping missing IDs and failing early if none remain. - Add scan-cache expiry via
--scan-cache-max-age-hours(default 24;0disables) and corresponding tests.
File summaries
| File | Description |
|---|---|
tests/test_archive_transcriber.py |
Adds regression tests for scan-cache expiry, CUDA failure behavior, and GPU index validation. |
src/python/tools/archive_transcriber.py |
Implements cache expiry, GPU index validation, and removes CPU fallback on CUDA init failure. |
scripts/run_archive_transcriber.sh |
Passes through TRANSCRIBE_MINUTES_BUDGET and sets a lower host-specific default. |
Review details
- Files reviewed: 3/3 changed files
- Comments generated: 2
- Review effort level: Lite
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Two hardening points from review: - init_gpu_assigner now clears the module-global assigner before configuring, so a previous one cannot survive a re-init without --gpus, and drops negative GPU indices with a warning -- "-1" previously sailed past the < device_count check and only failed at model load, one worker at a time. If nothing usable remains it raises as before. - --scan-cache-max-age-hours rejects negative, NaN and infinite values at parse time. Negative silently treated every cache as expired; NaN/inf silently never expired one, which is exactly how the stale-cache bug hid.
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WalkthroughThe archive transcriber now expires stale scan caches, validates GPU selections, reports CUDA initialization failures without CPU fallback, and accepts a configurable transcription-minute budget. ChangesArchive transcriber runtime
Estimated code review effort: 4 (Complex) | ~45 minutes Merge Risk: ⚪ Minimal · up to The changes prevent invalid GPU assignments from silently consuming host RAM and prevent indefinitely stale scan results; reported checks pass, and no actionable merge-blocking risk remains. Poem
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✅ Passed checks (4 passed)
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Actionable comments posted: 3
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Inline comments:
In `@src/python/tools/archive_transcriber.py`:
- Line 608: At the GPU re-initialization boundary in run(), reset the current
thread’s cached MODEL_HOLDER.models entry along with gpu_assigner and worker ID
before get_model() can reuse prior state, so each run reevaluates the current
CUDA configuration.
- Line 716: Update parse_args() to register --no-cuda with dest="use_cuda" and
action="store_false", while preserving existing --use-cuda compatibility. Add a
parser test confirming --no-cuda parses successfully and sets use_cuda to false.
- Line 1031: Add the --scan-cache-max-age-hours option to
archive_transcriber_remote.py and propagate its converted cache expiry value as
cache_max_age_seconds when calling discover_video_jobs(), preserving the
existing cache-expiration policy.
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scripts/run_archive_transcriber.shsrc/python/tools/archive_transcriber.pytests/test_archive_transcriber.py
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The CUDA-failure error message added in this branch tells operators to "pass --no-cuda deliberately", but only --use-cuda <bool> was registered -- the documented recovery command failed argument parsing. Add --no-cuda as a store_false alias of use_cuda. init_gpu_assigner also clears the calling thread's cached models and GPU assignment alongside the assigner. Worker threads are created fresh per run, so their thread-local models die with the executor; the calling thread's cache was the one that could serve a model built under a previous CUDA configuration if run() executes twice in-process.
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Three failure modes surfaced by the 2026-08-31 incident, where the VM was re-provisioned mid-day from two 15 GB vGPUs (31 GB RAM) to a single 24 GB L4-24Q (28 GB RAM), while the service was configured for
GPUS=0,1.1. Silent CPU fallback → OOM crash loop
Workers assigned to the removed GPU logged:
large-v3 on CPU loads ~6 GB of weights into host RAM per worker and runs orders of magnitude slower — the two CPU-fallback workers never finished a single video, drove load average to 60, and pushed RSS to 29 GB until the kernel killed the service, every ~40 minutes (8 kills on 2026-08-31 alone).
Fix: remove the fallback. CUDA init failure now raises with a clear message.
--no-cudastill selects CPU deliberately.2. No validation of configured GPU indices
init_gpu_assignernow checks configured indices againstctranslate2.get_cuda_device_count():run()exits 2 with the message rather than a traceback;3. Scan cache trusted forever
A cache written on 2026-01-23 was loaded verbatim for seven months. Every cycle reported
0 transcriptions, 0 translations neededwhile ~1,200 new videos accumulated unseen — the count143384appears in all 50 cycles logged since March because it was the same snapshot every time.Fix:
--scan-cache-max-age-hours(default 24,0disables). An expired cache is ignored with a warning and rebuilt by the normal scan path, so the next run is fast again.Run script
TRANSCRIBE_MINUTES_BUDGETenv passthrough, defaulting to 150 on this host: the tool's 220 default was sized against the 31 GB the box had before the re-provision cut it to 28 GB (peak RSS ≈ 13.5 GB floor + 0.44 GB + 0.055 GB per audio-minute in flight).Verification
ruff, mypy clean; 65 tests pass (7 new). Each fix was verified non-vacuous by reverting it and confirming its tests fail:
The three preserved behaviors (fresh cache trusted,
0disables expiry, fail-open on unknown device count) pass in both states, as intended.Deployed context
The box currently runs with a systemd drop-in (
GPUS=0 WORKERS=3) applied during the incident; this PR makes the code robust to the same class of event recurring.