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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 _get_upper_bound(self):
 r"""Return an upper bound on the eigenvalues of the Laplacian."""


        if self.lap_type == 'normalized':
            return 2  # Equal iff the graph is bipartite.
        elif self.lap_type == 'combinatorial':
            bounds = []
            # Equal for full graphs.
            bounds += [self.n_vertices * np.max(self.W)]
            # Gershgorin circle theorem. Equal for regular bipartite graphs.
            # Special case of the below bound.
            bounds += [2 * np.max(self.dw)]
            # Anderson, Morley, Eigenvalues of the Laplacian of a graph.
            # Equal for regular bipartite graphs.
            if self.n_edges > 0:
                sources, targets, _ = self.get_edge_list()
                bounds += [np.max(self.dw[sources] + self.dw[targets])]
            # Merris, A note on Laplacian graph eigenvalues.
            if not self.is_directed():
                W = self.W
            else:
                W = utils.symmetrize(self.W, method='average')
            m = W.dot(self.dw) / self.dw  # Mean degree of adjacent vertices.
            bounds += [np.max(self.dw + m)]
            # Good review: On upper bounds for Laplacian graph eigenvalues.
            return min(bounds)
        else:
            raise ValueError('Unknown Laplacian type '
                             '{}'.format(self.lap_type))