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Hi Xupeng ,
I was looking for how people use WGAN loss in implementation. I noticed that you use categorial_crossetropy. Is there any reason to that? isn't supposed to be like D_loss = tf.reduce_mean(D_real) - tf.reduce_mean(D_fake) ?
The text was updated successfully, but these errors were encountered:
Hi Xupeng ,
I was looking for how people use WGAN loss in implementation. I noticed that you use categorial_crossetropy. Is there any reason to that? isn't supposed to be like D_loss = tf.reduce_mean(D_real) - tf.reduce_mean(D_fake) ?
The text was updated successfully, but these errors were encountered: