Denoising Diffusion Probability Model

Install

pip install git+https://github.com/Qiyuan-Ge/joi.git

Image Generation

MNIST

• without guidence

python ddpm_train.py --n_epochs=200 --bs=128 --lr=1e-4 --timesteps=500 --wd=1e-4 --dropout=0.1 --dataset='mnist' --lr_decay=True --channels=1

• classifier free guidance

python ddpm_train.py --n_epochs=200 --bs=128 --lr=1e-4 --timesteps=500 --wd=1e-4 --dropout=0.1 --num_classes=10 --dataset='mnist' --lr_decay=True --channels=1

Cifar10

• classifier free guidance

python ddpm_train.py --n_epochs=800 --bs=64 --lr=1e-4 --timesteps=1000 --wd=1e-4 --dropout=0.1 --num_classes=10 --lr_decay=True

Super Resolution

Image Inpainting

Text-to-Image Generation

Multi GPU Training

accelerate config
accelerate launch ddpm_train.py

or

accelerate launch --multi_gpu ddpm_train.py

Log

2022/10/4 
add gradient clip
2022/10/8 
add p2 reweigh loss 
from <Perception Prioritized Training of Diffusion Models(https://arxiv.org/abs/2204.00227)>
2022/10/9
add cross attention 
from <CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification(https://arxiv.org/abs/2103.14899)> 

Reference

- Lil’Log
  https://lilianweng.github.io/posts/2021-07-11-diffusion-models/
- annotated-diffusion
  https://huggingface.co/blog/annotated-diffusion
- Improved Denoising Diffusion Probabilistic Models
  https://arxiv.org/abs/2102.09672
  https://github.com/openai/improved-diffusion
- Cascaded Diffusion Models for High Fidelity Image Generation
  https://arxiv.org/abs/2106.15282
- GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
  https://arxiv.org/abs/2112.10741
- Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
  https://arxiv.org/abs/2205.11487
- Hierarchical Text-Conditional Image Generation with CLIP Latents
- Perception Prioritized Training of Diffusion Models
  https://arxiv.org/abs/2204.00227