Minimal diffusion models - Minimal code and simple experiments to play with Denoising Diffusion Probabilistic Models (DDPMs)

Overview

Minimal code and simple experiments to play with Denoising Diffusion Probabilistic Models (DDPMs)

All experiments have tensorboard visualizations for samples / train curves etc.

  1. To run the toy data experiments:
python scripts/train_toy.py --dataset swissroll --save_path logs/swissroll
  1. 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
  1. To run the CIFAR image generation experiment:
python scripts/train_cifar.py --save_path logs/cifar
  1. To run the CelebA image generation experiments:
python scripts/train_celeba.py --save_path logs/celeba
Owner
Rithesh Kumar
AI Researcher @ Descript. Formerly Mila | MSR Montreal | Lyrebird
Rithesh Kumar
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