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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _build_prior(self, prior_tensors):
 """ Build a tf expression for the prior by summing all child-parameter priors. """

        # TODO(@awav): What prior must represent empty list of parameters?
        if not prior_tensors:
            return tf.constant(0, dtype=settings.float_type)
        return tf.add_n(prior_tensors, name='prior')