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Hi. I've found, that you unfreeze the whole GAN, and making steps only via specific optimizer (for generator and discriminator). But when you do loss.backward, gradients are computed for the WHOLE GAN, whereas for certain optimizer only their own gradients are needed. It causes additional memory uses and increased iteration time.
Please correct me if I am wrong.
The text was updated successfully, but these errors were encountered:
Hi. I've found, that you unfreeze the whole GAN, and making steps only via specific optimizer (for generator and discriminator). But when you do loss.backward, gradients are computed for the WHOLE GAN, whereas for certain optimizer only their own gradients are needed. It causes additional memory uses and increased iteration time.
Please correct me if I am wrong.
The text was updated successfully, but these errors were encountered: