style-based-gan-pytorch
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rosinality
about the image size
i choose ffhq-dataset's thumbnails128x128. I'm curious about which parameters need to be modified？should the --max_size in train.py be modified? should the number of layers in model.py be modified, such as only 6 layers instead of 9 layers?
You only need to adjust --max_size arguments. Number of layers will be adjusted accordingly.
You only need to adjust --max_size arguments. Number of layers will be adjusted accordingly.
thank you very much！And I I have another question：what is the function of FusedDownsample and Fusedupsample ? Why we need it if the resolution is more than 64px, but not if the resolution is less than 64px? I'm a little confused。
FusedUp(Down)sample is equivalent to conv + avgpool or nearest neighbor upsample + conv. In the official implementations it is used if resolution is larger than 64px as it is more performant at that resolutions. But I haven't measured the performance differences, though.
FusedUp(Down)sample is equivalent to conv + avgpool or nearest neighbor upsample + conv. In the official implementations it is used if resolution is larger than 64px as it is more performant at that resolutions. But I haven't measured the performance differences, though.
ok! Thanks, it helps me a lot