vintage-gan / AUTOMATION.md
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# Automation Notes
VintageGAN automation is intentionally conservative. Scripts may help with
training, testing, and evaluation, but the project does not claim zero-click
academic results.
Use automation only after:
- dependencies install cleanly,
- train/val data exists,
- the dataset license is recorded,
- tests pass,
- and a smoke run is successful.
Primary commands:
```bash
pytest tests -v
python training/pretrain.py --config configs/training_config.yaml --profile local_256
python training/gan_train.py --config configs/training_config.yaml --profile local_256 --generator-checkpoint checkpoints/generator_pretrain_best.pth
```
Automation outputs should be treated as valid only when the matching config,
metadata, checkpoint, and metrics artifact are saved.