'Note:
It returns a list, as one might use different weights for each
distribution.
Returns:
list[tf.Tensor]: entropy of each distribution.'

def entropy(self, x, theta):

    ret = []
    for (dist, xi, ti) in zip(self.dists, self._splitter(x, False), self._splitter(theta, True)):
        ret.append(dist.entropy(xi, ti))
    return ret
