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Cycle GAN

Cycle-GAN example in NNabla.

These are the example of generated images.

zebra zebra


Dataset is now automatically downloaded from the author's site when you run the following scripts.


python --device-id 0 \
                --context "cudnn" \
                --lambda-idt 0.5 \
                --monitor-path identity.monitor \
                --model-save-path identity.monitor

This will take about one day using one GeForce 1080 Ti, and you can find the result in identity.monitor.


python --device-id 0 \
               --context "cudnn" \
               --monitor-path identity.monitor.evaluation \
               --model-load-path identity.monitor/params_266799.h5

You can find the result of generated images in identity.monitor.evaluation for all corresponding test images.

For other settings of hyper parameters, see or simply run with -h option, or see the and


  • Examples do not use ReflectionPad. This is one of differences from the author's code.
  • [TODO] verification of training with datasets except for horse2zebra.


  1. Jun-Yan Zhu, Taesung Park, Phillip Isola, Alexei A. Efros, "Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks",
  2. Xudong Mao, Qing Li, Haoran Xie, Raymond Y.K. Lau, Zhen Wang, Stephen Paul Smolley, "Least Squares Generative Adversarial Networks",