Remove benchmark model weights after their last use #5

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kleb merged 2 commits from benchmark/model-weight-cleanup into main 2026-10-31 12:50:07 +01:00
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Benchmark runs accumulated model downloads until the kEmbed disks filled. Matrix lanes now finish one model across its assigned engines and datasets, then remove only downloads owned by that lane after their last use. Existing caches, supplied models, datasets and evidence stay intact; cleanup failures stop dispatch. Standalone runs retain caller-owned caches.

Proven with 331 passing Python tests, including cleanup lifecycle and ownership tests, plus Ruff checks and formatting. No inference or remote rollout was performed. Disk must still fit the largest single model.

Benchmark runs accumulated model downloads until the kEmbed disks filled. Matrix lanes now finish one model across its assigned engines and datasets, then remove only downloads owned by that lane after their last use. Existing caches, supplied models, datasets and evidence stay intact; cleanup failures stop dispatch. Standalone runs retain caller-owned caches. Proven with 331 passing Python tests, including cleanup lifecycle and ownership tests, plus Ruff checks and formatting. No inference or remote rollout was performed. Disk must still fit the largest single model.
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kReview review

Verdict: no findings

No verified defects were found in the reviewed changes.

kReview checked only the PR diff, metadata, and supplied repository context at 80e55f3a31. It reports only issues supported by this material.

Estimated cost: ~$0.14 total (401.3k in / 1.9k out); this run ~$0.08 (241.4k in / 817 out) / gpt-6.1-terra.

Run time: 1:01 total; this run 0:20.

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kleb merged commit 0547b45237 into main 2026-10-31 12:50:07 +01:00
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