Coding Stable Diffusion from scratch in PyTorch

Full coding of Stable Diffusion from scratch, with full explanation, including explanation of the mathematics. Visual explanation of text-to-image, image-to-image, inpainting Repository with PDF slides: https://github.com/hkproj/pytorch-stable-diffusion Prerequisites: 1) Transformer explained: https://www.youtube.com/watch?v=bCz4OMemCcA Chapters 00:00:00 - Introduction 00:04:30 - What is Stable Diffusion? 00:05:40 - Generative Models 00:12:07 - Forward and Reverse Process 00:17:44 - ELBO and Loss 00:20:30 - Generating New Data 00:22:20 - Classifier-Free Guidance 00:31:00 - CLIP 00:33:20 - Variational Auto Encoder 00:37:26 - Text to Image 00:39:54 - Image to Image 00:41:40 - Inpainting 00:44:30 - Coding the VAE 01:54:50 - Coding CLIP 02:09:10 - Coding the Unet 03:04:40 - Coding the Pipeline 03:53:00 - Coding the Scheduler (DDPM) 04:38:00 - Coding the Inference code