Comments (7)
that worked, thanks!
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The .pt models are pytorch checkpoints, they'll work with rosinality's stylegan2 code but not with the official implementations.
If you're working with SG3, you should just save the model as we do in this if block. This produces a pkl checkpoint that you can then use with the official SG3 code.
from stylegan-nada.
The .pt models are pytorch checkpoints, they'll work with rosinality's stylegan2 code but not with the official implementations.
If you're working with SG3, you should just save the model as we do in this if block. This produces a pkl checkpoint that you can then use with the official SG3 code.
when i try to use the generated pkl in stylegan3 it gives me an error (it only exports the save_intervals, not the actual trained model (training_iterations))
stylegan3 error =
Loading networks from "/content/drive/MyDrive/000150.pkl"...
Traceback (most recent call last):
File "/content/drive/MyDrive/WIP/stylegan3/gen_images.py", line 143, in <module>
generate_images() # pylint: disable=no-value-for-parameter
File "/usr/local/lib/python3.7/dist-packages/click/core.py", line 829, in __call__
return self.main(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/click/core.py", line 782, in main
rv = self.invoke(ctx)
File "/usr/local/lib/python3.7/dist-packages/click/core.py", line 1066, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/usr/local/lib/python3.7/dist-packages/click/core.py", line 610, in invoke
return callback(*args, **kwargs)
File "/content/drive/MyDrive/WIP/stylegan3/gen_images.py", line 108, in generate_images
G = legacy.load_network_pkl(f)['G_ema'].to(device) # type: ignore
File "/content/drive/MyDrive/WIP/stylegan3/legacy.py", line 40, in load_network_pkl
assert isinstance(data['G'], torch.nn.Module)
KeyError: 'G'
from stylegan-nada.
What StyleGAN3 script are you trying to run? If it's one of the generation scripts, could you try to change the loading code from:
with dnnlib.util.open_url(network_pkl) as f:
G = legacy.load_network_pkl(f)['G_ema'].to(device)
to:
with dnnlib.util.open_url(network_pkl) as f:
G = pickle.load(f)['G_ema'].to(device)
and let me know if that works?
You may also have to import pickle
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Glad to hear. Closing the issue. Feel free to re-open or open a new issue if you need more help.
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it seems like the colab only saves the previous save_interval, for example if i put the number of save_interval on for example 400 and training_iterations on 800 it only seems to save 000400.pkl and not 000800.pkl, how do i fix this? the model definitely exists somewhere because i can generate pictures with it but it doesn't appear anywhere
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Set the training_iterations to 801 and it should work get you that last checkpoint
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