From 56408f4a40711d77f0542a1f64be23726d5d81f9 Mon Sep 17 00:00:00 2001 From: Phil Wang Date: Sat, 30 Apr 2022 16:57:02 -0700 Subject: [PATCH] project management --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 354a89e..8cc1911 100644 --- a/README.md +++ b/README.md @@ -818,10 +818,10 @@ Once built, images will be saved to the same directory the command is invoked - [x] bring in vit-vqgan https://arxiv.org/abs/2110.04627 for the latent diffusion - [x] abstract interface for CLIP adapter class, so other CLIPs can be brought in - [x] take care of mixed precision as well as gradient accumulation within decoder trainer +- [x] just take care of the training for the decoder in a wrapper class, as each unet in the cascade will need its own optimizer - [ ] become an expert with unets, cleanup unet code, make it fully configurable, port all learnings over to https://github.com/lucidrains/x-unet - [ ] copy the cascading ddpm code to a separate repo (perhaps https://github.com/lucidrains/denoising-diffusion-pytorch) as the main contribution of dalle2 really is just the prior network - [ ] transcribe code to Jax, which lowers the activation energy for distributed training, given access to TPUs -- [ ] just take care of the training for the decoder in a wrapper class, as each unet in the cascade will need its own optimizer - [ ] train on a toy task, offer in colab - [ ] think about how best to design a declarative training config that handles preencoding for prior and training of multiple networks in decoder - [ ] extend diffusion head to use diffusion-gan (potentially using lightweight-gan) to speed up inference