My autoencoder model learns the most common patterns in images with pixel values -1, 0 or 1. While my model runs well, the decoding falls into a local minima with float values between -1 and 1. 

Is there anyway in Pytorch I can constrain the kernel filters to have entries -1, 0 or 1 to observe better learning capabilities?