Thanks a lot.
Now I can see why the generation results were same at different loss functions.
In fact there was only working criterion.
I’ll try to modify my code more elegantly.
BTW in second question, Does the loss function of D work properly?
I read various ACGAN codes in github, they designed the loss function of discriminator by adding 2 criterions of real and fake images.
And many answers in here about this, they said it is OK to add criterions like that.
In my case, I assigned the generated images as fake, and like to force the generator makes real(high resolution)-like images.
When I ran the code, there were some grads, but now I cannot say that is going well.