WassersteinGAN.tensorflow
WassersteinGAN.tensorflow copied to clipboard
shekkizh
Tensorflow implementation of Wasserstein GAN - arxiv: https://arxiv.org/abs/1701.07875
I don't understand how exactly the loss function in line 5 of algorithm 1 in the original WGAN paper is implemented here. In your code you **minimise** `self.discriminator_loss = discriminator_loss_fake...
My tensorflow version is 0.12.1 when I run run_main.py, I got this error "ValueError: Variable discriminator/disc_bn1/discriminator_1/disc_bn1/cond/discriminator_1/disc_bn1/moments/moments_1/mean/ExponentialMovingAverage/biased does not exist, or was not created with tf.get_variable(). Did you mean to set...
Thank you for sharing the code. Say if, D should maximise D(f)-D(r) , => minimising D(r)- D(f) and G should minimise D(f)-D(r) => minimising D(f). And your code also follows...
I have a question on the discriminator construction. I find the final number of channel is "1" via convolutional layer in this implementation. However, I find in others, e.g., "improved...
Hi. In this implementation, is batch normalization used in the discriminator? I think in WGAN paper, it is mentioned that you should not use BN in discriminators, right? In discriminators...
Excellent implement!!! I want to implement WGAN in Caffe. I have confused with the gradient computing of WGAN loss. Would you give some details of mathematical formulas? Thank you!
Dear Author Thanks a lot for providing the code of W-GAN. BTW, we want to know if there is any pre-trained W-GAN model for us to directly test without training?...
