Comments (3)
While I am unsure of the exact cause of your error, I will recommend that you ensure that your model's training images are properly loaded. I just cloned this repository and began training it on my custom dataset using all default settings except the --impl=cuda option, and everything appears to be working fine.
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So the error you mentioned is coming due to the loss ns_pathreg_r1() used for afhq and ffhq. Change the loss to ns_DiffAugment_r1() which doesn't need labels and it will work fine. Due to some unknown reason the number of labels are none when the model starts training while using the ns_pathreg_r1() loss.
from stylegan2.
I have tried many things to use GradientTape.gradient() but could not do it, I switch it to tf.gradients to use StyleGan2 ppl loss, it worked;
#from
pl_grads = pl_tape.gradient(pl_noise_applied, pl_w)
#to
pl_grads = tf.gradients(
ys=pl_noise_applied,
xs=pl_w
)[0]
from stylegan2.
Related Issues (2)
- PPL Weight file HOT 1
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