jgrusewski
|
2da5bafc0e
|
refactor: rename tli→fxt, delete legacy scripts/RunPod/deploy artifacts
- Rename tli/ directory to fxt/, update package + binary name to "fxt"
- Replace all `use tli::` → `use fxt::` across 52 Rust files
- Update build.rs proto paths (tli/proto → fxt/proto) in 6 services
- Update Dockerfiles, CI workflows, deploy.sh for new paths
- Delete ~170 legacy shell scripts (kept 15 essential ones)
- Delete RunPod Python client (runpod/), tests (tests/runpod/)
- Delete foxhunt-deploy crate (RunPod-only deployment tool)
- Delete terraform/runpod/ (moved to Scaleway)
- Delete ML Python hyperopt scripts (replaced by Rust Argmin PSO)
- Delete .gitlab-ci.yml (using GitHub + Gitea)
- Remove foxhunt-deploy from workspace members
504 files changed, -74,355 lines of legacy code removed.
Workspace compiles clean (0 errors, 0 warnings).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
|
2026-02-24 10:32:21 +01:00 |
|
jgrusewski
|
7458f1be01
|
feat(wave12): E2E validation complete - 225-feature pipeline ready
✅ Validation Results:
- PPO training: 24.2s (1 epoch, 950 samples, dim=225)
- Feature extraction: 105μs/bar (9.5x faster than target)
- Model checkpoint: 293KB (147KB actor + 146KB critic)
- GPU memory: 145MB used (96.4% headroom)
- Zero dimension mismatches
📊 Success Criteria (5/5):
✅ Feature dimension = 225 (Wave C 201 + Wave D 24)
✅ Model state_dim = 225
✅ Training completed without errors
✅ Checkpoint saved successfully
✅ No dimension mismatch errors
📁 Training Data Ready:
- ES.FUT: 2.9MB, 180 days
- NQ.FUT: 4.4MB, 180 days
- 6E.FUT: 2.8MB, 180 days
- ZN.FUT: 65KB, 90 days (clean)
🚀 Next: Full production model retraining (4 models, ~10min GPU time)
🤖 Generated with Claude Code (https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
|
2025-10-22 22:48:04 +02:00 |
|