Return the output from the experts.

    When one example goes to multiple experts, the outputs are summed.

    Args:
      x: a Tensor with shape [batch, num_experts, expert_capacity, depth]

    Returns:
      a `Tensor` with shape `[batch, length, depth]

def combine(self, x):
    """Return the output from the experts.

    When one example goes to multiple experts, the outputs are summed.

    Args:
      x: a Tensor with shape [batch, num_experts, expert_capacity, depth]

    Returns:
      a `Tensor` with shape `[batch, length, depth]
    """
    depth = tf.shape(x)[-1]
    x *= tf.expand_dims(self._nonpadding, -1)
    ret = tf.unsorted_segment_sum(
        x, self._flat_indices, num_segments=self._batch * self._length)
    ret = tf.reshape(ret, [self._batch, self._length, depth])
    return ret