Returns log det | dx / dy | = num_events * sum log | scale |.

def log_det_jacobian(self, inputs):
    """Returns log det | dx / dy | = num_events * sum log | scale |."""
    del inputs  # unused
    # Number of events is number of all elements excluding the batch and
    # channel dimensions.
    num_events = tf.reduce_prod(tf.shape(inputs)[1:-1])
    log_det_jacobian = num_events * tf.reduce_sum(self.log_scale)
    return log_det_jacobian