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tomguluson92 avatar tomguluson92 commented on June 14, 2024

Thanks a lot!
It has been a few months that I haven't kept pace with progress in PyTorch, could you please explain is there a difference between f = f[:, :, ::-1, ::-1] and torch.flip(f, [2, 3])?
The advice 2, 3 looks good to me, you could pull request a version to improve it and i will have it look and merge if it works well.

^.^
Samuel

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XiaoqiangZhou avatar XiaoqiangZhou commented on June 14, 2024

Thanks for your reply.
For the first problem, if you use [::-1] index for a torch.tensor, you will get an error ValueError: negative step not yet supported, i.e., cannot flip a torch.tensor like numpy array.
Besides, I'm working on this project and it will be my pleasure to pull a request later.

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tomguluson92 avatar tomguluson92 commented on June 14, 2024

Thanks for your reply.
For the first problem, if you use [::-1] index for a torch.tensor, you will get an error ValueError: negative step not yet supported, i.e., cannot flip a torch.tensor like numpy array.
Besides, I'm working on this project and it will be my pleasure to pull a request later.

Thanks!

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ulucsahin avatar ulucsahin commented on June 14, 2024

Thanks for your reimplementation!

  1. In networks_stylegan.py, line 107 f = f[:, :, ::-1, ::-1], I think you should consider use f = torch.flip(f, [2, 3])
  2. In networks_stylegan.py, line 247, x = self.noise(x, noise), I think you should consider add a condition judgement before this line, like if self.noise is not None:
  3. In defination of forward function of the class GBlock, do you miss a 3x3 convolution between upsmaple and the first adaIn1?

Did you find the answer for 3? I was thinking the same about missing a convolution between upsample and first adaln1 so I checked the issues and saw your question. I think the layer is missing as well but I haven't tested the code myself yet so I don't know if it works or not.

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