Functions from the constraints module allow setting constraints (eg. non-negativity) on network parameters during optimization.
The keyword arguments used for passing constraints to parameters in a layer will depend on the layer.
In the Dense layer it is simply W_constraint for the main weights matrix, and b_constraint for the bias.
from keras.constraints import maxnorm
model.add(Dense(64, 64, W_constraint = maxnorm(2)))