This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.
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I would like to ask what is the goal of the network trained using Main.py? #11
In the Diffusion.py file I see that
loss = F.mse_loss(self.model(x_t, t), x_0, reduction='none')
Does this mean that we want to train the Unet network to make the output images closer and closer to the noise? I don't really understand it here.
In the Diffusion.py file I see that loss = F.mse_loss(self.model(x_t, t), x_0, reduction='none') Does this mean that we want to train the Unet network to make the output images closer and closer to the noise? I don't really understand it here.