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gen_img
model
acgan_model.py
acgan_tb.png
acgan_train.py
readme.md

readme.md

Auxiliary Classifier Generative Adversarial Networks

Loss Function

  • used sce_loss with D/G nets
  • used softce_loss with C nets

Architecture Networks

  • Same with the AC-GAN paper.
  • But, i just used hyper-parameters like weight initializer, etc...
DIFFS AC-GAN Paper ME
weight initializer Isotropic Gaussian HE Initializer
Activation noise std 0 ~ 0.2 None

Isotropic Gaussian parameters : (µ = 0, σ = 0.02)
HE Initializer parameters : (factor = 1, FAN_AVG, uniform)

Tensorboard

result

Elapsed Time : 1h 17m 56s with GTX 1060 6GB x 1

Result

Name Global Step 10k Global Step 25k Global Step 50k
ACGAN img img img

To-Do

  • prevent model collapse. Sometimes it happens... :(
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