code: def _expectation(p, mean, none, kern, feat, nghp=None):
      
      return tf.matrix_transpose(expectation(p, (kern, feat), mean))
docs: Compute the expectation:
      expectation[n] = <x_n K_{x_n, Z}>_p(x_n)
          - K_{.,} :: Linear kernel
      or the equivalent for MarkovGaussian
  
      :return: NxDxM