I tired, using transforms.Lambda(), to even try to normalize data per pixel from the whole data set.
For some reason it made results worse though I’d think it would be better strategy.
I wonder about something, Let’s say the first layer is Linear Layer (Fully Connected).
What’s the point in removing the mean from the data, as there is a Bias term is is optimized, wouldn’t it calculate the best term to begin with?