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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def nativeCliqueEmbed(self, width):
 """Compute a maximum-sized native clique embedding in an induced subgraph of chimera with chainsize ``width+1``. If possible, returns a uniform choice among all largest cliques. INPUTS: width: width of the squares to search, also `chainlength-1` OUTPUT: clique: a list containing lists of qubits, each associated to a chain. These lists of qubits are carefully arranged so that 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) """

        def f(x):
            return x.nativeCliqueEmbed(width)
        objective = self._objective_bestscore
        return self._translate(self._map_to_processors(f, objective))