Anto01
cf454f6e40
- Add TrialManager (trial_manager.py) for consistent trial_NNNN naming - Add DashboardDB (dashboard_db.py) for Optuna-compatible database schema - Update CLAUDE.md with trial management documentation - Update ATOMIZER_CONTEXT.md with v1.8 trial system - Update cheatsheet v2.2 with new utilities - Update SYS_14 protocol to v2.3 with TrialManager integration - Add LAC learnings for trial management patterns - Add archive/README.md for deprecated code policy Key principles: - Trial numbers NEVER reset (monotonic) - Folders NEVER get overwritten - Database always synced with filesystem - Surrogate predictions are NOT trials (only FEA results) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
3 lines
1.2 KiB
JSON
3 lines
1.2 KiB
JSON
{"timestamp": "2025-12-24T08:13:38.642843", "category": "protocol_clarification", "context": "SYS_14 Neural Acceleration with dashboard integration", "insight": "When running neural surrogate turbo optimization, FEA validation trials MUST be logged to Optuna for dashboard visibility. Use optuna.create_study() with load_if_exists=True, then for each FEA result: trial=study.ask(), set params via suggest_float(), set objectives as user_attrs, then study.tell(trial, weighted_sum).", "confidence": 0.95, "tags": ["SYS_14", "neural", "optuna", "dashboard", "turbo"]}
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{"timestamp": "2025-12-28T10:15:00", "category": "protocol_clarification", "context": "SYS_14 v2.3 update with TrialManager integration", "insight": "SYS_14 Neural Acceleration protocol updated to v2.3. Now uses TrialManager for consistent trial_NNNN naming instead of iter{N}. Key components: (1) TrialManager for folder+DB management, (2) DashboardDB for Optuna-compatible schema, (3) Trial numbers are monotonically increasing and NEVER reset. Reference implementation: studies/M1_Mirror/m1_mirror_cost_reduction_flat_back_V5/run_turbo_optimization.py", "confidence": 0.95, "tags": ["SYS_14", "trial_manager", "dashboard_db", "v2.3"]}
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