How Can I Clip The Values Returned By A Layer In Keras?

How can I clip the values returned by the Lambda layer? I tried using this: from keras.backend.tensorflow_backend import clip from keras.layers.core import Lambda ... model.add(De

Solution 1:

It actually has to be implemented as loss, at the model.compile step.

from keras import backend as K

defclipped_mse(y_true, y_pred):
    return K.mean(K.square(K.clip(y_pred, 0., 1900.) - K.clip(y_true, 0., 1900.)), axis=-1)

model.compile(loss=clipped_mse)

EDIT: Actually, now in hindsight I think that this might not be the right approach. This actually means we do not add penalty for going over too high of a values - it's in a way the opposite of what we want.