# How model loss is computed from multiple outputs when loss_weights are set to zero?

If I set loss_weights = 0 for all multiple outputs of a Keras model, how the loss function is computed? I am aware from Keras documentation about the definition: "The loss value that will be minimized by the model will then be the weighted sum of all individual losses, weighted by the loss_weights coefficients" but in this situation, I wonder what is actually the model trying to minimize?

Also, I am interested to know if possible to optimize independently, model's outputs, without having to optimize the sum of individual losses.