Let’s say I have a sparse vector of ones and zeros (NxM) and I would like to have it as a dropout filter on the conv2d layer output which is also (NxM). Is it possible to achieve that by just multiplying it with the output?
Furthermore, is it possible to set a different dropout “mask” for each of the X batch samples? Or I would need to have X backprops by 1 batch sample?
Thank you.