Repository navigation
Handle MemoryError in submission pipeline - #15
Conversation
|
Caution Review failedThe pull request is closed. WalkthroughAdds MemoryError handling and instrumentation to arc_submit.solve_with_budget, extending metadata and logs, invoking gc per task, and tracking memory error counts. Documents the change in AGENTS.md and introduces a unit test validating fallback to best_so_far and memerror flag behavior. Changes
Sequence Diagram(s)sequenceDiagram
autonumber
actor Runner as Main/CLI
participant Submit as solve_with_budget
participant Solver as Solver
participant GC as gc
Note over Runner,Submit: Per task execution
Runner->>Submit: solve_with_budget(task, budget, solver)
Submit->>GC: gc.collect()
Submit->>Solver: solve_task_two_attempts(task, budget)
alt Success
Solver-->>Submit: result
Submit->>Runner: outputs, meta{timeout: false, memerror: false}
else Timeout
Solver-->>Submit: best_so_far(task)
Submit->>Runner: outputs from best_so_far, meta{timeout: true, memerror: false}
else MemoryError (new)
Solver--x Submit: MemoryError
Submit->>Solver: best_so_far(task)
Solver-->>Submit: fallback result
Submit->>Runner: outputs from best_so_far, meta{timeout: false, memerror: true}
end
Note right of Submit: Runner aggregates mem_error_count and logs per-task flags
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~25 minutes Poem
✨ Finishing touches
🧪 Generate unit tests
📜 Recent review detailsConfiguration used: CodeRabbit UI Review profile: CHILL Plan: Pro 📒 Files selected for processing (3)
Thanks for using CodeRabbit! It's free for OSS, and your support helps us grow. If you like it, consider giving us a shout-out. Comment |
Summary
solve_with_budgetand fall back to best-so-far predictiongc.collect()to free resourcesTesting
python -m py_compile arc_submit.pypytest tests/test_solve_with_budget_memory.py -qpytest test_beam_search_fix.py -qhttps://chatgpt.com/codex/tasks/task_e_68c5048f2e18832297e8b1c0856171a5
Summary by CodeRabbit