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* docs: update links to PL latest * also stable * last * Apply suggestions from code review * Apply suggestions from code review Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com> * fixing * . * fabric * fixing * . --------- Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com> |
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README.md | ||
train_fabric.py | ||
train_torch.py |
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 |
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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.