code: def expert_to_gates(self):
      
      return self._ep(
          tf.concat,
          transpose_list_of_lists(
              self._dp(lambda d: d.expert_to_gates(), self._dispatchers)), 0)
docs: Gate values corresponding to the examples in the per-expert `Tensor`s.
  
      Returns:
        a list of `num_experts` one-dimensional `Tensor`s of type `tf.float32`.