tensorflowkeras

Keras: Multiple outputs, loss only a function of one?

I have a setup like this:

model = keras.Model(input,[output1,output2])

My loss function is only a function of output1. How do I tell Keras to ignore output2 for the purposes of computing loss? The best I have come up with is to generate a bogus loss function which always returns 0.0:

model.compile(optimizer=..., loss=[realLossFunction, zeroLossFunction])

I can live with this, but I have to see the statistics and progress of this loss function all over the place and would like to know if there is a more elegant way.

Solution

  • You could just avoid putting this output in the model, and then reusing the weights (or sharing them with the functional API) to add the additional output to the full model.

    But using a zero loss is also fine.