I appreciate with your help, ptrblck However i have one more quick questions,
What is an ideal loss curve of G and D when i use the criterion as “torch.nn.BCELoss”?
criterion = torch.nn.BCELoss()
outputs= = D(real_images, y)
real_loss = criterion(outputs, real_labels)
outputs = D(fake_images, y)
fake_loss = criterion(outputs, fake_labels)     
d_loss = real_loss + fake_loss

g_loss = criterion(discriminator_outputs, real_labels)

Should both G_loss and D_loss be decreasing?
or D_loss should be decreasing while the G_loss should be increasing??
And Can i just sum real and fake loss for D_loss or should they be averaged for D_loss?
And my case, i want to generate numeric features with 12 dimensions like attached.
스크린샷 2020-01-19 오후 12.24.031728×1150 116 KB