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Chainer-GANs

Various GANs with Chainer

Requirement

  • Chainer==1.24.0
  • OpenCV

List

By default, all models are tested on the CelabA dataset. You can find the training results in corresponding folders.

Gradient Penalty

Most of recent GANs (WGAN-GP, CramerGAN, DRAGAN) contains the gradient norm regularization, this has been proved as a way to stabilize GAN training.

The current version of Chainer do not support high order derivatives, a solution is to manually implement the backward procedure with auto-differentiable chainer.functions. (Refer WGAN-GP codes for the details.)

  • L.Linear, L.Convolution2D, L.Deconvolution2D, F.leaky_relu, F.relu, F.sigmoid, F.tanh, L.LayerNormalization is implemented.
  • Some GAN papers suggest to use LayerNormalization instead on BatchNormalization in the discriminator in the case of gradient penalty.

Special thanks to mattya for the idea and reference codes.

Samples

Some DRAGAN results:

DRAGAN_2d_faces

DRAGAN_2d_Analogy



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