>I got to thinking, though: what if there was some minimum bound to the number of channels for the base layer of a diffusion network? >To test out this theory,

>I got to thinking, though: what if there was some minimum bound to the number of channels for the base layer of a diffusion network? >To test out this theory, I needed a way to compress the output of the diffusion model. One idea that came to mind is using the concepts behind PixelShuffle. So I compressed the waveform by 16x using a 1D form of PixelShuffle, increased the base dimensionality to 256, and started another training run. I'm not familiar with the author's previous projects or the terminology here. Do they just mean he increased the size of the first hidden layer and (base dimensionality to 256) and compressed the output layer by 16?