Phil Wang b693e0be03 default number of resnet blocks per layer in unet to 2 (in imagen it was 3 for base 64x64)

2022-05-30 10:06:48 -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

overhaul prior dataloader (#122)

2022-05-29 07:39:59 -07:00

__init__.py

unet_number on decoder trainer only needs to be passed in if there is greater than 1 unet, so that unconditional training of a single ddpm is seamless (experiment in progress locally)

2022-05-16 09:17:17 -07:00

cli.py

add missing import (#56)

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

dalle2_pytorch.py

default number of resnet blocks per layer in unet to 2 (in imagen it was 3 for base 64x64)

2022-05-30 10:06:48 -07:00

optimizer.py

use deterministic optimizer params (#116)

2022-05-25 09:31:43 -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

trackers.py

it was correct the first time, my bad

2022-05-20 18:05:15 -07:00

train_configs.py

make sure diffusion prior can be instantiated from pydantic class without clip

2022-05-26 08:47:30 -07:00

trainer.py

allow for one to stop grouping out weight decayable parameters, to debug optimizer state dict problem

2022-05-24 21:42:32 -07:00

utils.py

small cleanup

2022-05-22 15:39:38 -07:00

vqgan_vae_trainer.py

unet_number on decoder trainer only needs to be passed in if there is greater than 1 unet, so that unconditional training of a single ddpm is seamless (experiment in progress locally)

2022-05-16 09:17:17 -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