Buckets:
| #!/usr/bin/env python3 | |
| """Train the TCN model on FI-2010 or custom data. | |
| Usage: | |
| python scripts/train_tcn.py --data data/fi2010/ --epochs 50 | |
| """ | |
| import argparse | |
| import logging | |
| import sys | |
| from pathlib import Path | |
| # Add ml package to path | |
| # Insert the ml directory at the FRONT of sys.path | |
| ML_DIR = Path(__file__).resolve().parent.parent / "ml" | |
| sys.path.insert(0, str(ML_DIR)) | |
| PROJECT_ROOT = Path(__file__).resolve().parent.parent | |
| sys.path.insert(0, str(PROJECT_ROOT)) | |
| from flash_crash_watchdog.data.fi2010_loader import load_fi2010 | |
| from flash_crash_watchdog.models.stage3_tcn import Stage3TCN, TCNConfig | |
| def main() -> int: | |
| parser = argparse.ArgumentParser(description="Train the TCN model") | |
| parser.add_argument("--data", required=True, help="FI-2010 directory") | |
| parser.add_argument("--epochs", type=int, default=50) | |
| parser.add_argument("--output", default="models/tcn_baseline.pt") | |
| args = parser.parse_args() | |
| logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s") | |
| train_data, val_data = load_fi2010(args.data) | |
| model = Stage3TCN(TCNConfig()) | |
| history = model.train(train_data, val_data, epochs=args.epochs) | |
| output_path = Path(args.output) | |
| output_path.parent.mkdir(parents=True, exist_ok=True) | |
| model.save(output_path) | |
| print(f"Model saved to {output_path}") | |
| return 0 | |
| if __name__ == "__main__": | |
| raise SystemExit(main()) | |
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