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gen_img
model
readme.md
wgan_model.py
wgan_tb.png
wgan_train.py

readme.md

Wasserstein Generative Adversarial Networks

Loss Function

  • used sce loss at D/G nets.
  • used gradient penalty

Architecture Networks

  • Same with the WGAN paper.
DIFFS WGAN Paper ME
Networks Resnet like simple 4 conv nets

Tensorboard

result

Elapsed time : 1h 7m 7s with GTX 1060 6GB x 1

Result

Name Global Step 10k Global Step 25k Global Step 50k
WGAN-GP img img img

To-Do