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This project is mirrored from
https://github.com/lucidrains/gigagan-pytorch
. Pull mirroring updated
Sep 19, 2024
.
0.0.75
5af7e625
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quick fix for sampling from unet upsampler
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Jul 19, 2023
0.0.73
960d2ece
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make discriminator autofilter multiscale input resolutions that are greater...
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Jul 19, 2023
0.0.72
c73870f1
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make sure to sample the EMA version as well, if available
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Jul 19, 2023
0.0.71
b17fd17b
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add a dropout on the fmap for auxiliary reconstruction, increase learning rate
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Jul 19, 2023
0.0.70
f46cc19c
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add optimizer support for adam and adam with weight decay
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Jul 19, 2023
0.0.68
7ea14283
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cleanup
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Jul 19, 2023
0.0.67
857c12fc
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address
https://github.com/lucidrains/gigagan-pytorch/issues/26
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Jul 19, 2023
0.0.66
f06f9e21
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release and appreciate
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Jul 19, 2023
0.0.65
e7a266ae
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oops, adaptive kernel inputs need to account for expansion of batch by number...
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Jul 18, 2023
0.0.64
94b0ee09
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allow for only predicting a fraction across batch-scale dimension for multi-scale logits
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Jul 18, 2023
0.0.63
b30e9163
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allow for calculating multiscale loss only every so number of steps
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Jul 18, 2023
0.0.62
ba7fcc88
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allow for specifying what fraction of feature maps, across flattened batch -...
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Jul 18, 2023
0.0.61
57947659
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some improvements for auxiliary reconstruction
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Jul 18, 2023
0.0.60
045405f4
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complete text conditioned training for both base generator as well as upsampler
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Jul 18, 2023
0.0.59
6b3338df
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make sure multiscale can be turned off
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Jul 17, 2023
0.0.58
c149ffdd
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need gradient penalty on multiscale output or it blows up. scale the gradient...
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Jul 17, 2023
0.0.57
fc47028c
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hook up generator learning from the multi-scale logits
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Jul 17, 2023
0.0.56
2bdf505c
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do not gradient penalize contributions from multi-scale logits; seem to be much more stable
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Jul 17, 2023
0.0.55
84d92a17
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add hinge losses to multi-scale outputs, also apply gradient penalty on those...
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Jul 17, 2023
0.0.54
dcefb168
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just cycle shuffled dataloader by default
·
Jul 17, 2023
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