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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
The text was updated successfully, but these errors were encountered:
@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...
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
The text was updated successfully, but these errors were encountered: