Yep, it’s true for the case of manifold learning but sklearn (I don’t wanna be to harsh on it) has very bad implementation that raises errors in some particular cases and doesn’t use the optimal approach. For instance check the issues I raised on github  for more in regards to tsne implementation & LLE.
But in the case of rnn package I guess you’ll have to roll your own.