examples/fabric/dcgan/README.md
This is an example of a GAN (Generative Adversarial Network) that learns to generate realistic images of faces. We show two code versions: The first one is implemented in raw PyTorch, but isn't easy to scale. The second one is using Lightning Fabric to accelerate and scale the model.
Tip: You can easily inspect the difference between the two files with:
sdiff train_torch.py train_fabric.py
| Real | Generated |
|---|---|
Raw PyTorch:
python train_torch.py
Accelerated using Lightning Fabric:
python train_fabric.py
Generated images get saved to the outputs folder.
The CelebA dataset is hosted through a Google Drive link by the authors, but the downloads are limited. You may get a message saying that the daily quota was reached. In this case, manually download the data through your browser.