I have a tensor which has empty values.  I want to apply a 2d blurring convolution kernel just to the non-empty values. For simplicity let’s assume kernel weights are all equal.
Maybe something like dynamic kernel weights, so kernel weights = 1/n, where n is the number of valid pixels in the region.
Is there currently pytorch functionality which supports something like this?