Denoising Diffusion Implicit Models

This is a pytorch implementation of DDIM. The original paper is here https://arxiv.org/abs/2010.02502 .

This code is almost identical to DDPM, see here: https://github.com/Alokia/diffusion-DDPM-pytorch

how to use

Almost all the parameters that can be modified are listed in the config.yml file. You can modify the relevant parameters as needed, and then run the train.py file to start training.

After training, run the generate.py file to generate the results. These are the parameters of generate.py :

• -cp : the path of checkpoint.
• --device : device used. 'cuda' (default) or 'cpu'.
• --sampler : sampler method, can be 'ddpm'(default) or 'ddim'.
• -bs : how many images to generate at once. Default 16.
• --result_only : whether to output only the generated results. Default False.
• --interval : extract an image every how many steps. Only valid without the result_only parameter. Default 50.
• --eta : ddim parameter, $\eta$ in the paper. Default 0.0.
• --steps : ddim sampling steps. Default 100.
• --method : ddim sampling method. can be 'linear'(default) or 'quadratic'.
• --nrow : how many images are displayed in a row. Only valid with the result_only parameter. Default 4.
• --show : whether to display the result image. Default False.
• -sp : save path of the result image. Default None.
• --to_grayscale : convert images to grayscale. Default False.

Some generated images

• MNIST，click to download checkpoint

python generate.py -cp "checkpoint/mnist.pth" -bs 16 --interval 3 --show -sp
"data/result/mnist_sampler.png" --sampler "ddim" --steps 50

python generate.py -cp "checkpoint/mnist.pth" -bs 256 --show -sp "data/result/mnist_result.png" --nrow 16 --result_only --sampler "ddim" --steps 50

• CIFAR10, click to download checkpoint

python generate.py -cp "checkpoint/cifar10.pth" -bs 16 --interval 10 --show -sp "data/result/cifar10_sampler.png" --sampler "ddim" --steps 200 --method "quadratic"

python generate.py -cp "checkpoint/cifar10.pth" -bs 256 --show -sp "data/result/cifar10_result.png" --nrow 16 --result_only --sampler "ddim" --steps 200 --method "quadratic"