Mehta trained as an equation where we're integrating out the these sufficient statistics of our meta training data called theta and this implies the assumption that Phi is conditionally independent of D meta train given theta which is very reasonable because we just said the theta should be whatever extracts all the necessary sufficient statistics from D meta train now in reality integrating out theta is computationally very very expensive so we wouldn't want to do this what we would want to do in practice typically