Phil Wang 14e63a3f67 also offer l2norm clamping in diffusion prior during training, if one were using predict x0 objective

2022-05-06 10:05:14 -07:00

..

data

bring in the simple tokenizer released by openai, but also plan on leaving room for custom tokenizer with yttm

2022-04-12 09:23:17 -07:00

dataloaders

Add a dataloader for training the decoder (#57)

2022-05-05 07:08:45 -07:00

__init__.py

add diffusion prior trainer, which automatically takes care of the exponential moving average (training and sampling), as well as mixed precision, gradient clipping

2022-05-06 08:11:09 -07:00

cli.py

add missing import (#56)

2022-05-04 07:42:20 -07:00

dalle2_pytorch.py

also offer l2norm clamping in diffusion prior during training, if one were using predict x0 objective

2022-05-06 10:05:14 -07:00

optimizer.py

now completely OpenAI CLIP compatible for training

2022-04-29 13:05:01 -07:00

tokenizer.py

bring in the simple tokenizer released by openai, but also plan on leaving room for custom tokenizer with yttm

2022-04-12 09:23:17 -07:00

train_vqgan_vae.py

port over vqgan vae trainer

2022-05-01 08:09:15 -07:00

train.py

add diffusion prior trainer, which automatically takes care of the exponential moving average (training and sampling), as well as mixed precision, gradient clipping

2022-05-06 08:11:09 -07:00

vqgan_vae.py

remove convnext blocks, they are illsuited for generative work, validated by early experimental results at https://github.com/lucidrains/video-diffusion-pytorch

2022-05-05 07:07:21 -07:00