Finetune on single-channel without its repeating
Hi,I want to finetune the diffusion model on my dataset. My images are greyscaled, so they have only one channel.I already successfully finetune it using np.repeat for each image.But I am wondering is there a way to make it better, faster, and more efficient?I want to finetune the model without channel duplication (np.repeat).I tried to reduce weights dimensions using slicing/mean/max.  For example, from [3, 128, 128] to [1, 128, 128], from [3] to [1] for bias.But in this case, after each denoise step, I got the same noize image as it was after adding the noise step. So it did not denoised properly.I much appreciate any help or suggestion with this. Is the problem in the noise/denoise step or in the weights dimension reducing itself?
2023-04-20T15:53:00Z
I much appreciate any advice