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README.md
data_loader.py
main.py
models.py
params.py
utils.py

README.md

WGAN (Wasserstein GAN)

This script implements the paper Wasserstein GAN.

Usage

Run python3 main.py to start training WGAN.

Structure

  • data_loader.py: dataset setting and data loader.
  • models.py: discriminator and generator network model.
  • params.py: parameters for the training process.
  • utils.py: some useful fuctions for training.

Result

  • Images from CIFAR-10 dataset:

    WGAN-real_samples

  • Images generated by WGAN (100 iters, use BatchNorm):

    WGAN-fake-100-686