lightning/examples/fabric/dcgan
Jirka Borovec 2f087ae30e
docs: update broken links & latest/stable (#16994)
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Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>

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Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>
2023-03-15 20:19:41 +01:00
..
README.md docs: update broken links & latest/stable (#16994) 2023-03-15 20:19:41 +01:00
train_fabric.py Restructure Lite examples and add GAN (#16240) 2023-01-05 14:07:43 +00:00
train_torch.py Restructure Lite examples and add GAN (#16240) 2023-01-05 14:07:43 +00:00

README.md

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
sample-data fake-7914

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