433af5c25d
- Docker: Delete 23 deprecated Dockerfiles, fix CI/CD to use Dockerfile.foxhunt-build - Config: Remove 36 .env files, keep 4 essential, delete config/environments/ - Docs: Archive 614 Wave D files to docs/archive/wave_d/, 95% reduction in root - Scripts: Delete 56 deprecated scripts, keep 58 production-critical (49% reduction) - Python: Organize 37 scripts into scripts/python/ subdirectories, delete ml/python/ - Build: Remove 1GB artifacts, delete old venvs, clean Python cache from git - Migrations: Delete deprecated directory (4,432 lines), remove duplicate database/migrations/ - Infrastructure: Delete deployment/ (61 files), docs/scripts/ (8 files) Total impact: ~2,500 files cleaned, 750MB+ space freed, zero production impact All deleted scripts backed up to archives. runpod/ and tests/runpod/ preserved. data_acquisition_service retained per user request.
2.4 KiB
2.4 KiB
ML Test Suite - Module Breakdown Report
Date: 2025-10-25 Total Tests: 1,324 passing Status: ✅ PRODUCTION READY
Core ML Models
DQN (Deep Q-Network)
- Tests: 94 passing
- Status: ✅ All tests passing
- Coverage: Action selection, experience replay, Rainbow components, batch processing
PPO (Proximal Policy Optimization)
- Tests: 7 passing
- Status: ✅ All tests passing
- Coverage: GAE advantages, reward computation, GPU batch limits
MAMBA-2 (Selective State Space Model)
- Tests: 5 passing
- Status: ✅ All tests passing
- Coverage: Config conversion, memory estimation, trainer creation
TFT (Temporal Fusion Transformer)
- Tests: 86 passing
- Status: ✅ All tests passing (FP32 + INT8-PTQ)
- Coverage: 225-feature support, quantization, checkpointing, OOM recovery
- Note: QAT tests exist separately (24 tests, compilation blocked)
TLOB (Temporal Limit Order Book)
- Tests: 11 passing
- Status: ✅ All tests passing
- Coverage: MBP10 feature extraction, transformer predictions
Feature Engineering
Feature Extraction Pipeline
- Tests: 294 passing
- Status: ✅ All 225 features validated
- Coverage: Waves A-D (foundational, alternative bars, advanced, regime-adaptive)
Regime Detection
- Tests: 68 passing
- Status: ✅ All tests passing
- Coverage: CUSUM, transitions, adaptive strategies, orchestrator
Infrastructure & Support
Backtesting
- Tests: 4 passing
- Coverage: Sharpe ratio, drawdown, variance calculations
Batch Processing
- Tests: 19 passing
- Coverage: SIMD operations, memory pools, auto-tuning
Benchmarking
- Tests: 80 passing
- Coverage: Batch size finder, stability validator, memory profiler
Checkpointing
- Tests: 38 passing
- Coverage: Compression, signing, validation, versioning
Data Loaders
- Tests: 16 passing
- Coverage: DBN, streaming, calibration, TLOB loaders
Training Infrastructure
- Tests: 17 passing
- Coverage: Orchestrator, unified trainer, LR schedules
Summary Statistics
| Category | Tests | Percentage |
|---|---|---|
| Core ML Models | 203 | 15.3% |
| Feature Engineering | 362 | 27.3% |
| Infrastructure | 174 | 13.1% |
| Other | 585 | 44.1% |
| TOTAL | 1324 | 100% |