James Betker
1d5f4f6102
Crossgan
2020-08-07 21:03:39 -06:00
James Betker
fd7b6ca0a9
Comptue gan_grad_branch....
2020-08-06 12:11:40 -06:00
James Betker
30b16d5235
Update how branch GAN grad is disseminated
2020-08-06 11:13:02 -06:00
James Betker
be272248af
More RAGAN fixes
2020-08-05 16:47:21 -06:00
James Betker
26a6a5d512
Compute grad GAN loss against both the branch and final target, simplify pixel loss
...
Also fixes a memory leak issue where we weren't detaching our loss stats when
logging them. This stabilizes memory usage substantially.
2020-08-05 12:08:15 -06:00
James Betker
299ee13988
More RAGAN fixes
2020-08-05 11:03:06 -06:00
James Betker
b8a4df0a0a
Enable RAGAN in SPSR, retrofit old RAGAN for efficiency
2020-08-05 10:34:34 -06:00
James Betker
3c0a2d6efe
Fix grad branch debug out
2020-08-04 16:43:43 -06:00
James Betker
ec2a795d53
Fix multistep optimizer (feeding from wrong config params)
2020-08-04 16:42:58 -06:00
James Betker
4bfbdaf94f
Don't recompute generator outputs for D in standard operation
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Should significantly improve training performance with negligible
results differences.
2020-08-04 11:28:52 -06:00
James Betker
11b227edfc
Whoops
2020-08-04 10:30:40 -06:00
James Betker
6d25bcd5df
Apply fixes to grad discriminator
2020-08-04 10:25:13 -06:00
James Betker
c7e5d3888a
Add pix_grad_branch loss to metrics
2020-08-03 16:21:05 -06:00
James Betker
0d070b47a7
Add simplified SPSR architecture
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Basically just cleaning up the code, removing some bad conventions,
and reducing complexity somewhat so that I can play around with
this arch a bit more easily.
2020-08-03 10:25:37 -06:00
James Betker
47e24039b5
Fix bug that makes feature loss run even when it is off
2020-08-02 20:37:51 -06:00
James Betker
328afde9c0
Integrate SPSR into SRGAN_model
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SPSR_model really isn't that different from SRGAN_model. Rather than continuing to re-implement
everything I've done in SRGAN_model, port the new stuff from SPSR over.
This really demonstrates the need to refactor SRGAN_model a bit to make it cleaner. It is quite the
beast these days..
2020-08-02 12:55:08 -06:00
James Betker
c139f5cd17
More torch 1.6 fixes
2020-07-31 17:03:20 -06:00
James Betker
a66fbb32b6
Fix fixed_disc DataParallel issue
2020-07-31 16:59:23 -06:00
James Betker
bcebed19b7
Fix pixdisc bugs
2020-07-31 16:38:14 -06:00
James Betker
eb11a08d1c
Enable disjoint feature networks
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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
7629cb0e61
Add FDPL Loss
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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
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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
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
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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
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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
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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
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
8a9f215653
Huge set of mods to support progressive generator growth
2020-07-18 14:18:48 -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
1b1431133b
Add DualOutputSRG
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Also removes the old multi-return mechanism that Generators support.
Also fixes AttentionNorm.
2020-07-14 09:28:24 -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
0b7193392f
Implement unet disc
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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
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- 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
James Betker
5e8b52f34c
Misc changes
2020-07-10 09:45:48 -06:00
James Betker
12da993da8
More fixes...
2020-07-08 22:07:09 -06:00
James Betker
7d6eb28b87
More fixes
2020-07-08 22:00:57 -06:00
James Betker
b2507be13c
Fix up pixgan loss and pixdisc
2020-07-08 21:27:48 -06:00