denoising-diffusion-pytorch
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Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Hi diffusion developers, Thank you for the open source development! I have a naive question about the objective "pred_x_start". If we use this objective, after training we have a model...
Greate repo! Could you please tell me how large the size of a 1D dataset should be ( have files with 250 time-steps)? In your paper it is stated that...
Hi @lucidrains , I wonder post-training, how we can load EMA weight of models for generation. Does `trainer.load()` automatically give you EMA weight? Thank you.
When should the model be saved, and how should it be implemented? I use torch.save(self.unet.state_dict(), f"{self.savepath}unet_checkpoint_{timestamp}_epoch_{epoch}.pth") and torch.save(self.diffusion.state_dict(), f"{self.savepath}diffusion_checkpoint_{timestamp}_epoch_{epoch}.pth") to separately store the weights of the unet and diffusion models....
hi there, does this implemenation work for greyscale images dataset? and what changes would we need to do for using own greyscale dataset
Hello, which .py file are the training and testing files? Also, aren't there pre-trained weights?
Hello, I basically gave an input image, add noise to t=100, and then sample it back to t=1. I got these generated images with pure blue/green parts. Any ideas why...
Can diffusion model be used into image to image translation ?
I encountered an error while training the model. Specifically, during the save and sample process, the following error occurred: ``` pytorch/denoising_diffusion_pytorch/attend.py:77: UserWarning: Expected query, key and value to all be...