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:

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.