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kwonminki / Asyrp_official

official repo for Asyrp : Diffusion Models already have a Semantic Latent Space (ICLR2023)
MIT License
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Custom dataset training (P2 weighting) #10

Open ozgurkara99 opened 1 year ago

ozgurkara99 commented 1 year ago

Hello,

I have trained a diffusion model with a custom dataset using P2 weighting (the training code in the guided_diffusion folder), however, the generated samples are not correct when I use the functions (denoisin_step, generalized_steps) you have used in the main script. However, when I use the sampling codes in guided_diffusion/gaussian_diffusion.py module, it correctly generates samples. So could you please provied the details about how you trained CelebA_P2 model so that I can train my own dataset using P2 weighting with the same settings you trained in order to make it run with the sampling codes in your code?

Thanks

sidney1505 commented 1 year ago

@ozgurkara99 did you find a solution for the problem? I tried it the other way around doing inference with the pretrained models and that also did not work...