mrq/DL-Art-School
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bcebed19b7
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215 Commits

Author SHA1 Message Date
James Betker
bcebed19b7 Fix pixdisc bugs 2020-07-31 16:38:14 -06:00
James Betker
eb11a08d1c Enable disjoint feature networks 
This is done by pre-training a feature net that predicts the features
of HR images from LR images. Then use the original feature network
and this new one in tandem to work only on LR/Gen images.
 2020-07-31 16:29:47 -06:00
James Betker
6e086d0c20 Fix fixed_disc 2020-07-31 15:07:10 -06:00
James Betker
d5fa059594 Add capability to have old discriminators serve as feature networks 2020-07-31 14:59:54 -06:00
James Betker
6b45b35447 Allow multi_step_lr_scheduler to load a new LR schedule when restoring state 2020-07-31 11:21:11 -06:00
James Betker
e37726f302 Add feature_model for training custom feature nets 2020-07-31 11:20:39 -06:00
James Betker
7629cb0e61 Add FDPL Loss 
New loss type that can replace PSNR loss. Works against the frequency domain
and focuses on frequency features loss during hr->lr conversion.
 2020-07-30 20:47:57 -06:00
James Betker
85ee64b8d9 Turn down feadisc intensity 
Honestly - this feature is probably going to be removed soon, so backwards
compatibility is not a huge deal anymore.
 2020-07-27 15:28:55 -06:00
James Betker
ebb199e884 Get rid of safety valve (probably being encountered in val) 2020-07-26 22:51:59 -06:00
James Betker
d09ed4e5f7 Misc fixes 2020-07-26 22:44:24 -06:00
James Betker
c54784ae9e Fix feature disc log item error 2020-07-26 22:25:59 -06:00
James Betker
9a8f227501 Allow separate dataset to pushed in for GAN-only training 2020-07-26 21:44:45 -06:00
James Betker
b06e1784e1 Fix SRG4 & switch disc 
"fix". hehe.
 2020-07-25 17:16:54 -06:00
James Betker
e6e91a1d75 Add SRG4 
Back to the idea that maybe what we need is a hybrid
approach between pure switches and RDB.
 2020-07-24 20:32:49 -06:00
James Betker
3320ad685f Fix mega_batch_factor not set for test 2020-07-24 12:26:44 -06:00
James Betker
c50cce2a62 Add an abstract, configurabler weight scheduling class and apply it to the feature weight 2020-07-23 17:03:54 -06:00
James Betker
9ccf771629 Fix feature validation, wrong device 
Only shows up in distributed training for some reason.
 2020-07-23 10:16:34 -06:00
James Betker
bba283776c Enable find_unused_parameters for DistributedDataParallel 
attention_norm has some parameters which are not used to compute grad,
which is causing failures in the distributed case.
 2020-07-23 09:08:13 -06:00
James Betker
dbf6147504 Add switched discriminator 
The logic is that the discriminator may be incapable of providing a truly
targeted loss for all image regions since it has to be too generic
(basically the same argument for the switched generator). So add some
switches in! See how it works!
 2020-07-22 20:52:59 -06:00
James Betker
106b8da315 Assert that temperature is set properly in eval mode. 2020-07-22 20:50:59 -06:00
James Betker
c74b9ee2e4 Add a way to disable grad on portions of the generator graph to save memory 2020-07-22 11:40:42 -06:00
James Betker
e3adafbeac Add convert_model.py and a hacky way to add extra layers to a model 2020-07-22 11:39:45 -06:00
James Betker
7f7e17e291 Update feature discriminator further 
Move the feature/disc losses closer and add a feature computation layer.
 2020-07-20 20:54:45 -06:00
James Betker
46aa776fbb Allow feature discriminator unet to only output closest layer to feature output 2020-07-19 19:05:08 -06:00
James Betker
8a9f215653 Huge set of mods to support progressive generator growth 2020-07-18 14:18:48 -06:00
James Betker
47a525241f Make attention norm optional 2020-07-18 07:24:02 -06:00
James Betker
ad97a6a18a Progressive SRG first check-in 2020-07-18 07:23:26 -06:00
James Betker
b08b1cad45 Fix feature decay 2020-07-16 23:27:06 -06:00
James Betker
3e7a83896b Fix pixgan debugging issues 2020-07-16 11:45:19 -06:00
James Betker
a1bff64d1a More fixes 2020-07-16 10:48:48 -06:00
James Betker
240f254263 More loss fixes 2020-07-16 10:45:50 -06:00
James Betker
6cfa67d831 Fix featuredisc broadcast error 2020-07-16 10:18:30 -06:00
James Betker
8d061a2687 Add u-net discriminator with feature output 2020-07-16 10:10:09 -06:00
James Betker
0c4c388e15 Remove dualoutputsrg 
Good idea, didn't pan out.
 2020-07-16 10:09:24 -06:00
James Betker
4bcc409fc7 Fix loadSRG2 typo 2020-07-14 10:20:53 -06:00
James Betker
1e4083a35b Apply temperature mods to all SRG models 
(Honestly this needs to be base classed at this point)
 2020-07-14 10:19:35 -06:00
James Betker
7659bd6818 Fix temperature equation 2020-07-14 10:17:14 -06:00
James Betker
853468ef82 Allow legacy state_dicts in srg2 2020-07-14 10:03:45 -06:00
James Betker
1b1431133b Add DualOutputSRG 
Also removes the old multi-return mechanism that Generators support.
Also fixes AttentionNorm.
 2020-07-14 09:28:24 -06:00
James Betker
a2285ff2ee Scale anorm by transform count 2020-07-13 08:49:09 -06:00
James Betker
dd0bbd9a7c Enable AttentionNorm on SRG2 2020-07-13 08:38:17 -06:00
James Betker
4c0f770f2a Fix inverted temperature curve bug 2020-07-12 11:02:50 -06:00
James Betker
14d23b9d20 Fixes, do fake swaps less often in pixgan discriminator 2020-07-11 21:22:11 -06:00
James Betker
ba6187859a err5 2020-07-10 23:02:56 -06:00
James Betker
902527dfaa err4 2020-07-10 23:00:21 -06:00
James Betker
020b3361fa err3 2020-07-10 22:57:34 -06:00
James Betker
b3a2c21250 err2 2020-07-10 22:52:02 -06:00
James Betker
716433db1f err1 2020-07-10 22:50:56 -06:00
James Betker
0b7193392f Implement unet disc 
The latest discriminator architecture was already pretty much a unet. This
one makes that official and uses shared layers. It also upsamples one additional
time and throws out the lowest upsampling result.

The intent is to delete the old vgg pixdisc, but I'll keep it around for a bit since
I'm still trying out a few models with it.
 2020-07-10 16:24:42 -06:00
James Betker
812c684f7d Update pixgan swap algorithm 
- Swap multiple blocks in the image instead of just one. The discriminator was clearly
  learning that most blocks have one region that needs to be fixed.
- Relax block size constraints. This was in place to gaurantee that the discriminator
  signal was clean. Instead, just downsample the "loss image" with bilinear interpolation.
  The result is noisier, but this is actually probably healthy for the discriminator.
 2020-07-10 15:56:14 -06:00