Phil Wang 49de72040c fix decoder trainer optimizer loading (since there are multiple for each unet), also save and load step number correctly

2022-05-22 15:21:00 -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

Update decoder dataloader (#105)

2022-05-20 16:38:55 -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

accept unets as list for decoder

2022-05-20 20:31:26 -07:00

optimizer.py

Added single GPU training script for decoder (#108)

2022-05-20 19:46:19 -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

let the pydantic config base model take care of loading configuration from json path

2022-05-22 14:47:23 -07:00

trainer.py

fix decoder trainer optimizer loading (since there are multiple for each unet), also save and load step number correctly

2022-05-22 15:21:00 -07:00

utils.py

small cleanup with timer

2022-05-20 20:05:01 -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