mrq/DL-Art-School
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7eaabce48d
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36 Commits

Author SHA1 Message Date
James Betker
7eaabce48d Full resnet corrupt, no BN 
And it works! Thanks fixup..
 2020-04-30 19:17:30 -06:00
James Betker
03258445bc tblogger.. 2020-04-30 12:35:51 -06:00
James Betker
b6e036147a Add more batch norms to FlatProcessorNet_arch 2020-04-30 11:47:21 -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
f027e888ed Clear out tensorboard on job restart. 2020-04-30 11:44:53 -06:00
James Betker
b7857f35c3 Enable skip-through connections from disc to gen 2020-04-30 11:30:11 -06:00
James Betker
bf634fc9fa Make resnet w/ BN discriminator use leaky relus 2020-04-30 11:28:59 -06:00
James Betker
3781ea725c Add Resnet Discriminator with BN 2020-04-29 20:51:57 -06:00
James Betker
a5188bb7ca Remover fixup code from arch_util 
Going into it's own arch.
 2020-04-29 15:17:43 -06:00
James Betker
5b8a77f02c Discriminator part 1 
New discriminator. Includes spectral norming.
 2020-04-28 23:00:29 -06:00
James Betker
2c145c39b6 Misc changes 2020-04-28 11:50:16 -06:00
James Betker
46f550e42b Change downsample_dataset to do no image modification 
I'm  preprocessing the images myself now. There's no need to have
the dataset do this processing as well.
 2020-04-28 11:50:04 -06:00
James Betker
8ab595e427 Add FlatProcessorNet 
After doing some thinking and reading on the subject, it occurred to me that
I was treating the generator like a discriminator by focusing the network
complexity at the feature levels. It makes far more sense to process each conv
level equally for the generator, hence the FlatProcessorNet in this commit. This
network borrows some of the residual pass-through logic from RRDB which makes
the gradient path exceptionally short for pretty much all model parameters and
can be trained in O1 optimization mode without overflows again.
 2020-04-28 11:49:21 -06:00
James Betker
b8f67418d4 Retool HighToLowResNet 
The receptive field of the original was *really* low. This new one has a
receptive field of 36x36px patches. It also has some gradient issues
that need to be worked out
 2020-04-26 01:13:42 -06:00
James Betker
02ff4a57fd Enable HighToLowResNet to do a 1:1 transform 2020-04-25 21:36:32 -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
ea54c7618a Print error when image read fails 2020-04-23 23:59:32 -06:00
James Betker
e98d92fc77 Allow test to operate on batches 2020-04-23 23:59:09 -06:00
James Betker
8ead9ae183 Lots more config files 2020-04-23 23:58:27 -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
12d92dc443 Add GTLQ dataset 2020-04-22 00:40:38 -06:00
James Betker
4d269fdac6 Support independent PIX dataroot 2020-04-22 00:40:13 -06:00
James Betker
05aafef938 Support variant input sizes and scales 2020-04-22 00:39:55 -06:00
James Betker
ebda70fcba Fix AMP 2020-04-22 00:39:31 -06:00
James Betker
f4b33b0531 Some random fixes/adjustments 2020-04-22 00:38:53 -06:00
James Betker
2538ca9f33 Add my own configs 2020-04-22 00:37:54 -06:00
James Betker
af5dfaa90d Change GT_size to target_size 2020-04-22 00:37:41 -06:00
James Betker
cc834bd5a3 Support >128px image squares 2020-04-21 16:32:59 -06:00
James Betker
4f6d3f0dfb Enable AMP optimizations & write sample train images to folder. 2020-04-21 16:28:06 -06:00
PRAGMA
1fb12871fd
Create requirements.txt 2019-11-24 07:48:52 +00:00
XintaoWang
a25ee9464d test w/o GT 2019-09-01 22:20:10 +08:00
XintaoWang
0098663b6b SRGAN model supprots dist training 2019-09-01 22:14:29 +08:00
XintaoWang
866a858e59 add deform_conv_cuda_kernel.cu 2019-08-27 17:49:12 +08:00
XintaoWang
037933ba66 mmsr 2019-08-23 21:42:47 +08:00