No, You just need to define your loss function in keras environment, like you have to use their functions to be able to train. Here is just a simple example
import keras def my_loss(y_true, y_pred): # any actions you need to do with the arguments result = ... # you will have to use backend's functions of keras return result model.compile(loss=my_loss, ...)
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