lightning/examples/fabric/dcgan

DCGAN

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

Run

Raw PyTorch:

python train_torch.py

Accelerated using Lightning Fabric:

python train_fabric.py

Generated images get saved to the outputs folder.

Notes

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.

References

• DCGAN Tutorial
• Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
• Large-scale CelebFaces Attributes (CelebA) Dataset