| images | ||
| .gitignore | ||
| classifier.py | ||
| ddpm.py | ||
| loader.py | ||
| positionEncoding.py | ||
| README.md | ||
| sample.py | ||
| train_classifier.py | ||
| train.py | ||
| training.ini | ||
| unet.py | ||
DDPM
A Simple implementation of DDPM model in PyTorch.
It's just for fun, the Unet model does not include attention, normalization, etc.
Classifier Guidence DDPM
ref: Diffusion Models Beat GANs on Image Synthesis (https://arxiv.org/abs/2105.05233)
Traning
Before training, please set up the config.ini file:
[unet]
batch_size = 256
time_emb_dim = 128
device = cuda
epoch_num = 500
learning_rate = 1e-4
[ddpm]
iteration = 500
To start training, run:
$ python train.py
Sampling
To generate 16 pictures, run the following command:
The pictures will be output to the ./output directory.
$ python sample 16 # unconditional
$ python sample 16 7 # condiditional, want to generate "7" pictures



