Conditional anyres-gan implementation failure

[WenjinFu]

I am working on generating conditional food images but met some errors on loading labels for patch data. I strictly follow the instructions in the file "train.sh" and "train.py". In the first stage of training, I first tried to leverage the pre-trained network of conditional stylegan3 to train the patch datasets in stage two and I got the following errors:

And it is caused by None type tensor as you can see from the terminal output messages.
I read the paper, the authors use the unconditional image generation method. But I want to know if this method is compatible with conditional image generation.

[chail]

We only tried unconditional generation, but it should be compatible with the proper modifications. I suppose you'll need to modify the function compute_scale_inputs; in particular the mapped_scale = G.scale_mapping(scale, None). Here I'm assuming that G.c_dim is None (for unconditional generation), but you could have it also take in a class latent for class-conditional generation.