James Betker
17dd99b29b
Fix bug with discriminator noise addition
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It wasn't using the scale and was applying the noise to the
underlying state variable.
2020-09-20 12:00:27 -06:00
James Betker
3138f98fbc
Allow discriminator noise to be injected at the loss level, cleans up configs
2020-09-19 21:47:52 -06:00
James Betker
e9a39bfa14
Recursively detach all outputs, even if they are nested in data structures
2020-09-19 21:47:34 -06:00
James Betker
fe82785ba5
Add some new architectures to ssg
2020-09-19 21:47:10 -06:00
James Betker
b83f097082
Get rid of get_debug_values from RRDB, rectify outputs
2020-09-19 21:46:36 -06:00
James Betker
e0bd68efda
Add ImageFlowInjector
2020-09-19 10:07:00 -06:00
James Betker
e2a146abc7
Add in experiments hook
2020-09-19 10:05:25 -06:00
James Betker
9a17ade550
Some convenience adjustments to ExtensibleTrainer
2020-09-17 21:05:32 -06:00
James Betker
9963b37200
Add a new script for loading a discriminator network and using it to filter images
2020-09-17 13:30:32 -06:00
James Betker
723754c133
Update attention debugger outputting for SSG
2020-09-16 13:09:46 -06:00
James Betker
0918430572
SSG network
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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
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
ccf8438001
SPSR5
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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
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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
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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
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It didn't work anyways, so why not?
2020-09-11 16:09:28 -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
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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
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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
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- 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
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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
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
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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
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
44c75f7642
Undo SRG change
2020-09-04 17:32:16 -06:00
James Betker
6657a406ac
Mods needed to support training a corruptor again:
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- 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
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Greatly reduces memory consumption with a low performance penalty
2020-09-04 15:32:00 -06:00
James Betker
696242064c
Use tensor checkpointing to drastically reduce memory usage
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This comes at the expense of computation, but since we can use much larger
batches, it results in a net speedup.
2020-09-03 11:33:36 -06:00