Commit Graph

31 Commits

Author SHA1 Message Date
James Betker
299d855b34 Enable forced learning rates 2020-06-07 16:56:05 -06:00
James Betker
726d1913ac Allow validating in batches, remove val size limit 2020-06-02 08:41:22 -06:00
James Betker
8355f3d1b3 Only log discriminator data when gan is activated 2020-06-01 15:48:16 -06:00
James Betker
a38dd62489 Only train discriminator/gan losses when gan_w > 0 2020-06-01 15:09:10 -06:00
James Betker
446322754a Support generators that don't output intermediary values. 2020-05-23 21:09:54 -06:00
James Betker
f911ef0d3e Add corruptor_usage_probability
Governs how often a corruptor is used, vs feeding uncorrupted images.
2020-05-16 09:05:43 -06:00
James Betker
635c53475f Restore swapout models just before a checkpoint 2020-05-16 07:45:19 -06:00
James Betker
a33ec3e22b Fix skips & images samples
- Makes skip connections between the generator and discriminator more
  extensible by adding additional configuration options for them and supporting
  1 and 0 skips.
- Places the temp/ directory with sample images from the training process appear
  in the training directory instead of the codes/ directory.
2020-05-15 13:50:49 -06:00
James Betker
61ed51d9e4 Improve corruptor logic: switch corruptors randomly 2020-05-14 23:14:32 -06:00
James Betker
a946483f1c Fix discriminator noise floor 2020-05-14 20:45:06 -06:00
James Betker
c8ab89d243 Add model swapout
Model swapout is a feature where, at specified intervals,
a random D and G model will be swapped in place for the
one being trained. After a short period of time, this model
is swapped back out. This is intended to increase training
diversity.
2020-05-13 16:53:38 -06:00
James Betker
e36f22e14a Allow "corruptor" network to be specified
This network is just a fixed (pre-trained) generator
that performs a corruption transformation that the
generator-in-training is expected to undo alongside
SR.
2020-05-13 15:26:55 -06:00
James Betker
fc3ec8e3a2 Add a noise floor to th discriminator noise factor 2020-05-13 09:19:22 -06:00
James Betker
06d18343f7 Allow noise to be added to discriminator inputs 2020-05-12 16:25:38 -06:00
James Betker
9210a62f58 Add rotating log buffer to trainer
Should stabilize stats output.
2020-05-12 10:09:45 -06:00
James Betker
574e7e882b Fix up OOM issues when running a disjoint D update ratio and megabatches 2020-05-06 17:25:25 -06:00
James Betker
9f4581aacb Fix megabatch scaling, log low and med-res gen images 2020-05-05 08:34:57 -06:00
James Betker
3b4e54c4c5 Add support for passthrough disc/gen
Add RRDBNetXL, which performs processing at multiple image sizes.
Add DiscResnet_passthrough, which allows passthrough of image at different sizes for discrimination.
Adjust the rest of the repo to allow generators that return more than just a single image.
2020-05-04 14:01:43 -06:00
James Betker
44b89330c2 Support inference across batches, support inference on cpu, checkpoint
This is a checkpoint of a set of long tests with reduced-complexity networks. Some takeaways:
1) A full GAN using the resnet discriminator does appear to converge, but the quality is capped.
2) Likewise, a combination GAN/feature loss does not converge. The feature loss is optimized but
    the model appears unable to fight the discriminator, so the G-loss steadily increases.

Going forwards, I want to try some bigger models. In particular, I want to change the generator
to increase complexity and capacity. I also want to add skip connections between the
disc and generator.
2020-05-04 08:48:25 -06:00
James Betker
8341bf7646 Enable megabatching 2020-05-02 17:46:59 -06:00
James Betker
66e91a3d9e Revert "Enable skip-through connections from disc to gen"
This reverts commit b7857f35c3.
2020-04-30 11:45:07 -06:00
James Betker
b7857f35c3 Enable skip-through connections from disc to gen 2020-04-30 11:30:11 -06:00
James Betker
35bd1ecae4 Config changes for discriminator advantage run
Still going from high->low, discriminator discerns on low. Next up disc works on high.
2020-04-25 11:24:28 -06:00
James Betker
d95808f4ef Implement downsample GAN
This bad boy is for a workflow where you train a model on disjoint image sets to
downsample a "good" set of images like a "bad" set of images looks. You then
use that downsampler to generate a training set of paired images for supersampling.
2020-04-24 00:00:46 -06:00
James Betker
ea5f432f5a Log total gen loss 2020-04-22 14:02:10 -06:00
James Betker
79aff886b5 Modifications that allow developer to explicitly specify a different image set for PIX and feature losses 2020-04-22 10:11:14 -06:00
James Betker
4d269fdac6 Support independent PIX dataroot 2020-04-22 00:40:13 -06:00
James Betker
ebda70fcba Fix AMP 2020-04-22 00:39:31 -06:00
James Betker
4f6d3f0dfb Enable AMP optimizations & write sample train images to folder. 2020-04-21 16:28:06 -06:00
XintaoWang
0098663b6b SRGAN model supprots dist training 2019-09-01 22:14:29 +08:00
XintaoWang
037933ba66 mmsr 2019-08-23 21:42:47 +08:00