Hi Farhan!



 farhanrahman:

So essentially my ground truth dimension for a single image is 1000x1000x12. Each pixel has a vector of 12 float values where these values indicate certain properties. So this is not a classification problem but can be thought of as regression.
…
I am using 12 output channels at the final layer.


I assume that you mean you have 12 output channels per pixel in
the final layer.  Otherwise I don’t understand what you are doing.


Also I have read about the BCEWITHLOGITSLOSS, and I think it is the most fitting loss function in this context.


Given that you understand this to be similar to a regression,
MSELoss (mean-squared error) would be the appropriate loss
function.
(I can’t comment on Unet nor your CudaOutOfMemory error.)
Best.
K. Frank