Spectral Normalization for Keras Dense and Convolution Layers
The simple Keras implementation of ICLR 2018 paper, Spectral Normalization for Generative Adversarial Networks. [openreview][arixiv][original code(chainer)]
10epoch | With SN | Without SN |
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100epoch | With SN | Without SN |
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200epoch | With SN | Without SN |
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300epoch | With SN | Without SN |
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400epoch | With SN | Without SN |
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500epoch | with SN | without SN |
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Loss | with SN | without SN |
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Without GP |
10epoch | With SN | Without SN |
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With GP | ||
Without GP |
100epoch | With SN | Without SN |
---|---|---|
With GP | ||
Without GP |
200epoch | With SN | Without SN |
---|---|---|
With GP | ||
Without GP |
300epoch | With SN | Without SN |
---|---|---|
With GP | ||
Without GP |
400epoch | With SN | Without SN |
---|---|---|
With GP | ||
Without GP |
500epoch | with SN | without SN |
---|---|---|
With GP | ||
Without GP |
Loss | with SN | without SN |
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With GP | ||
Without GP |
from SpectralNormalizationKeras import DenseSN, ConvSN1D, ConvSN2D, ConvSN3D
CIFAR10 with DCGAN architecture
CIFAR10 with ResNet architecture