Hey!
So I explained as short as I could not to be punished by @ptrblck with my explaitives 
Every filter with that code is printed in black and white (as you are normalizing only one channel and one filter at a time) and only the convolution layer that inputs 3 channels (normally the first layer which inputs RGB images) will make a filter torch with the right size for making an RGB filter image (3xFxF beeing f the size of filter) otherwise your filters will make no sense (for ex. trying to divide a 64 channel filter joining 3 channels at a time) but you can try and see what kind of RGB image you make!
For your second question: filters = weights on a convolution layer, you will only get those with a trained model. I imagine you already did this if you are visualizing them! Maybe your are seeking to visualize the activation map?
Cheers!