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Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-01 22:50:38 +01:00

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# ml_training_service
Model training orchestration and lifecycle management for DQN, PPO, TFT, Mamba2, TLOB, and Liquid models with progress tracking and artifact storage.
## Key Types
- `MlTrainingServiceImpl` -- main gRPC service
- `JobTracker` -- training job state machine
- `CheckpointManager` -- model artifact persistence
## Features
- `minimal` (default) -- minimal ML feature set for financial models
- `gpu` -- SIMD GPU acceleration (requires CUDA)
- `mock-data` -- mock training data (testing, bypasses database)
## Configuration
- `GRPC_PORT` -- gRPC listen port
- `DATABASE_URL` -- PostgreSQL for job metadata and training history
- Prometheus metrics on port 9094
## Testing
```bash
SQLX_OFFLINE=true cargo test -p ml_training_service --lib
```