James Betker 6c6e82406e Pass a corruption factor through the dataset into the upsampling network ... The intuition is this will help guide the network to make better informed decisions about how it performs upsampling based on how it perceives the underlying content. (I'm giving up on letting networks detect their own quality - I'm not convinced it is actually feasible)		2021-06-07 09:13:54 -06:00
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.idea	IDEA update	2020-05-19 09:35:26 -06:00
data	Pass a corruption factor through the dataset into the upsampling network	2021-06-07 09:13:54 -06:00
models	Pass a corruption factor through the dataset into the upsampling network	2021-06-07 09:13:54 -06:00
scripts	CIFAR stuff	2021-06-05 14:16:02 -06:00
trainer	Don't do wandb except on rank 0	2021-06-06 16:52:07 -06:00
utils	Support gaussian diffusion models	2021-06-02 21:47:32 -06:00
multi_modal_train.py	More adjustments to support distributed training with teco & on multi_modal_train	2020-10-27 20:58:03 -06:00
process_video.py	misc	2021-01-23 13:45:17 -07:00
requirements.txt	Log eval to wandb	2021-06-04 23:23:20 -06:00
test_image_patch_classifier.py	More refactoring	2020-12-18 09:18:34 -07:00
test.py	misc adjustments for stylegan	2021-04-21 18:14:17 -06:00
train.py	Don't do wandb except on rank 0	2021-06-06 16:52:07 -06:00