Hydrino / ACGAN_mnist

An Auxiliary Classifier GAN (ACGAN) in pytorch to generate MNIST digits.

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ACGAN_mnist

An Auxiliary Classifier GAN(ACGAN) in PyTorch to generate MNIST digits.

Literature survey

Tips

Keep in mind that these tips are those which worked in this specific project. These may or may not work if you are generating stuff other than MNIST digits.

General

  • Keep the architectures of G and D symmetric.
  • Use ReLU in G and BatchNorm + LReLU in D.
  • Add dropout layers in D to make it 'weaker'.

Things that drastically improved performance

  • Label smoothing for D
  • Label flipping for D
  • Adding Dropout layers in G

Results

  • epoch 2 iteration 200/700 images/epoch2iter200

  • epoch 4 iteration 500/700 images/epoch2iter200

  • epoch 6 iteration 500/700 images/epoch2iter200

  • epoch 8 iteration 400/700 images/epoch2iter200

  • epoch 10 iteration 200/700 images/epoch2iter200

About

An Auxiliary Classifier GAN (ACGAN) in pytorch to generate MNIST digits.


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