code: def largestNativeClique(self, max_chain_length=None):
          
          def f(x):
              return x.largestNativeClique(max_chain_length=max_chain_length)
          objective = self._objective_bestscore
          return self._translate(self._map_to_processors(f, objective))
docs: Returns the largest native clique embedding we can find on the
          processor, with the shortest chainlength possible (for that clique
          size).  If possible, returns a uniform choice among all largest
          cliques.
  
          INPUTS:
              max_chain_length (int): longest chain length to consider or ``None`` if chain
              lengths are allowed to be unbounded.  (default: ``None``)
  
          OUTPUT:
              clique (list): a list containing lists of qubits, each associated to a
              chain.  These lists of qubits are carefully arranged so that
  
              >>> [zip(chain,chain[1:]) for chain in clique]
  
              is a list of valid couplers.
  
          Note: this fails to return a uniform choice if there are broken
          intra-cell couplers between working qubits. (the choice is
          uniform on a particular subprocessor)