This repository provides a PyTorch implementation of DDPM, a generative modeling approach that estimates gradients of the data distribution through denoising score matching, then uses Langevin sampling to generate samples. The implementation includes a U-Net architecture with support for flash attention and supports training diffusion models for image generation tasks.