We are currently implementing a WaveNet like structure to solve the problem of MNIST prediction, ie. given some part of the image, to reconstruct the rest. We’ve trained on the whole MNIST data set for starters, however we run into some problems regarding our model output estimate, namely that it is all gray.
From what we gather of info on PyTorch documentation we want to use binary cross entropy, and our model will use softmax on the output. Does Binary_cross_entropy use softmax, like Cross_entropy? We also tried to use the sigmoid, as the BCELoss function seemed to use it, but to no avail.