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Author SHA1 Message Date
James Betker
f5cd23e2d5 Further patch size adjustments 2020-09-16 16:50:35 -06:00
James Betker
723754c133 Update attention debugger outputting for SSG 2020-09-16 13:09:46 -06:00
James Betker
0b047e5f80 Increase scale of the patch selector random distribution 
This will cause larger slices of an image to appear more frequently,
increasing the difficulty of the generator.
 2020-09-16 08:27:42 -06:00
James Betker
f211575e9d Save models before validation 
Validation often fails with OOM, wasting hours of training time.
Save models first.
 2020-09-16 08:17:17 -06:00
James Betker
0918430572 SSG network 
This branches off of SPSR. It is identical but substantially reduced
in complexity. It's intended to be my long term working arch.
 2020-09-15 20:59:24 -06:00
James Betker
c833bd1eac Misc changes 2020-09-15 20:57:59 -06:00
James Betker
6deab85b9b Add BackboneEncoderNoRef 2020-09-15 16:55:38 -06:00
James Betker
d0321ca5de Don't load amp state dict if amp is disabled 2020-09-14 15:21:42 -06:00
James Betker
94deab2792 Fix error serving gt_fullsize_ref in full_image_dataset 2020-09-14 15:05:44 -06:00
James Betker
ccf8438001 SPSR5 
This is SPSR4, but the multiplexers have access to the output of the transformations
for making their decision.
 2020-09-13 20:10:24 -06:00
James Betker
5b85f891af Only log the name of the first network in the total_loss training set 2020-09-12 16:07:09 -06:00
James Betker
fb595e72a4 Supporting infrastructure in ExtensibleTrainer to train spsr4 
Need to be able to train 2 nets in one step: the backbone will be entirely separate
with its own optimizer (for an extremely low LR).

This functionality was already present, just not implemented correctly.
 2020-09-11 22:57:06 -06:00
James Betker
4e44bca611 SPSR4 
aka - return of the backbone! I'm tired of massively overparameterized generators
with pile-of-shit multiplexers. Let's give this another try..
 2020-09-11 22:55:37 -06:00
James Betker
19896abaea Clean up old SwitchedSpsr arch 
It didn't work anyways, so why not?
 2020-09-11 16:09:28 -06:00
James Betker
4c2ee66fe4 Fix video processor 2020-09-11 13:10:14 -06:00
James Betker
50ca17bb0a Feature mode -> back to LR fea 2020-09-11 13:09:55 -06:00
James Betker
1086f0476b Fix ref branch using fixed filters 2020-09-11 08:58:35 -06:00
James Betker
8c469b8286 Enable memory checkpointing 2020-09-11 08:44:29 -06:00
James Betker
5189b11dac Add combined dataset for training across multiple datasets 2020-09-11 08:44:06 -06:00
James Betker
313424d7b5 Add new referencing discriminator 
Also extend the way losses work so that you can pass
parameters into the discriminator from the config file
 2020-09-10 21:35:29 -06:00
James Betker
9e5aa166de Report the standard deviation of ref branches 
This patch also ups the contribution
 2020-09-10 16:34:41 -06:00
James Betker
668bfbff6d Back to best arch for spsr3 2020-09-10 14:58:14 -06:00
James Betker
992b0a8d98 spsr3 with conjoin stage as part of the switch 2020-09-10 09:11:37 -06:00
James Betker
e0fc5eb50c Temporary commit - noise 2020-09-09 17:12:52 -06:00
James Betker
00da69d450 Temporary commit - ref 2020-09-09 17:09:44 -06:00
James Betker
df59d6c99d More spsr3 mods 
- Most branches get their own noise vector now.
- First attention branch has the intended sole purpose of raw image processing
- Remove norms from joiner block
 2020-09-09 16:46:38 -06:00
James Betker
747ded2bf7 Fixes to the spsr3 
Some lessons learned:
- Biases are fairly important as a relief valve. They dont need to be everywhere, but
  most computationally heavy branches should have a bias.
- GroupNorm in SPSR is not a great idea. Since image gradients are represented
   in this model, normal means and standard deviations are not applicable. (imggrad
   has a high representation of 0).
- Don't fuck with the mainline of any generative model. As much as possible, all
   additions should be done through residual connections. Never pollute the mainline
   with reference data, do that in branches. It basically leaves the mode untrainable.
 2020-09-09 15:28:14 -06:00
James Betker
0ffac391c1 SPSR with ref joining 2020-09-09 11:17:07 -06:00
James Betker
c41dc9a48c Add missing requirements 2020-09-09 10:46:08 -06:00
James Betker
3027e6e27d Enable amp to be disabled 2020-09-09 10:45:59 -06:00
James Betker
c04f244802 More mods 2020-09-08 20:36:27 -06:00
James Betker
dffbfd2ec4 Allow SRG checkpointing to be toggled 2020-09-08 15:14:43 -06:00
James Betker
e6207d4c50 SPSR3 work 
SPSR3 is meant to fix whatever is causing the switching units
inside of the newer SPSR architectures to fail and basically
not use the multiplexers.
 2020-09-08 15:14:23 -06:00
James Betker
5606e8b0ee Fix SRGAN_model/fullimgdataset compatibility 1 2020-09-08 11:34:35 -06:00
James Betker
22c98f1567 Move MultiConvBlock to arch_util 2020-09-08 08:17:27 -06:00
James Betker
146ace0859 CSNLN changes (removed because it doesnt train well) 2020-09-08 08:04:16 -06:00
James Betker
f43df7f5f7 Make ExtensibleTrainer compatible with process_video 2020-09-08 08:03:41 -06:00
James Betker
a18ece62ee Add updated spsr net for test 2020-09-07 17:01:48 -06:00
James Betker
55475d2ac1 Clean up unused archs 2020-09-07 11:38:11 -06:00
James Betker
e8613041c0 Add novograd optimizer 2020-09-06 17:27:08 -06:00
James Betker
a5c2388368 Use lower LQ image size when it is being fed in 2020-09-06 17:26:32 -06:00
James Betker
b1238d29cb Fix trainable not applying to discriminators 2020-09-05 20:31:26 -06:00
James Betker
21ae135f23 Allow Novograd to be used as an optimizer 2020-09-05 16:50:13 -06:00
James Betker
912a4d9fea Fix srg computer bug 2020-09-05 07:59:54 -06:00
James Betker
0dfd8eaf3b Support injectors that run in eval only 2020-09-05 07:59:45 -06:00
James Betker
17aa205e96 New dataset that reads from lmdb 2020-09-04 17:32:57 -06:00
James Betker
44c75f7642 Undo SRG change 2020-09-04 17:32:16 -06:00
James Betker
6657a406ac Mods needed to support training a corruptor again: 
- Allow original SPSRNet to have a specifiable block increment
- Cleanup
- Bug fixes in code that hasnt been touched in awhile.
 2020-09-04 15:33:39 -06:00
James Betker
bfdfaab911 Checkpoint RRDB 
Greatly reduces memory consumption with a low performance penalty
 2020-09-04 15:32:00 -06:00
James Betker
8580490a85 Reduce usage of resize operations when not needed in dataloaders. 2020-09-04 15:31:24 -06:00