Tweedie Loss for Keras
I end up implementing something like this:

def tweedieloss(y_true, y_pred):
    p=1.5
    dev = 2 * (K.pow(y_true, 2-p)/((1-p) * (2-p)) -
                   y_true * K.pow(y_pred, 1-p)/(1-p) +
                   K.pow(y_pred, 2-p)/(2-p))
    return K.mean(dev)


which I don't know how right it is, for now it seems to be working.