Minimal code and simple experiments to play with Denoising Diffusion Probabilistic Models (DDPMs)
All experiments have tensorboard visualizations for samples / train curves etc. To run the toy data experiments: python scripts/train_toy.py –dataset swissroll –save_path logs/swissroll To run the discrete mode collapse experiment: python scripts/train_mnist.py –save_path logs/mnist_3 –n_stack 3 This requires the pretrained mnist classifier: python scripts/train/mnist_classifier.py To run the CIFAR image generation experiment: python scripts/train_cifar.py –save_path logs/cifar To run the CelebA image generation experiments: python scripts/train_celeba.py –save_path logs/celeba GitHub
Read more