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main.py #8

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ghost opened this issue Oct 31, 2018 · 1 comment
Open

main.py #8

ghost opened this issue Oct 31, 2018 · 1 comment

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@ghost
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ghost commented Oct 31, 2018

I wonder why in the main.py , you use the # when train discriminator

fake_map = generator(batch_img)

inp_d = torch.cat((batch_img,fake_map),1)

outputs = discriminator(inp_d)

d_fake_loss = loss_function(outputs, fake_labels)

print('D_fake_loss = ', d_fake_loss.data[0])

@IceClear
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IceClear commented Dec 9, 2018

I also wonder why he doesn't freeze generator's parameters when training the discriminator and the discriminator's parameters are not freezed when training the generator. Do you have any idea?

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