code: def laplacian_lambda_max(g):
      """Return the largest eigenvalue of the normalized symmetric Laplacian of a graph.
  
      If the graph is batched from multiple graphs, return the list of the largest eigenvalue
      for each graph instead.
  
      Parameters
      ----------
      g : DGLGraph
          The input graph, it must be a bi-directed homogeneous graph, i.e., every edge
          should have an accompanied reverse edge in the graph.
          The graph can be batched from multiple graphs.
  
      Returns
      -------
      list[float]
          A list where the i-th item indicates the largest eigenvalue
          of i-th graph in :attr:`g`.
  
          In the case where the function takes a single graph, it will return a list
          consisting of a single element.
  
      Examples
      --------
      >>> import dgl
      >>> g = dgl.graph(([0, 1, 2, 3, 4, 0, 1, 2, 3, 4], [1, 2, 3, 4, 0, 4, 0, 1, 2, 3]))
      >>> dgl.laplacian_lambda_max(g)
      [1.809016994374948]
      """
      g_arr = batch.unbatch(g)
      rst = []
      for g_i in g_arr:
          n = g_i.num_nodes()
          adj = g_i.adj_external(
              transpose=True, scipy_fmt=g_i.formats()["created"][0]
          ).astype(float)
          norm = sparse.diags(
              F.asnumpy(g_i.in_degrees()).clip(1) ** -0.5, dtype=float
          )
          laplacian = sparse.eye(n) - norm * adj * norm
          rst.append(
              scipy.sparse.linalg.eigs(
                  laplacian, 1, which="LM", return_eigenvectors=False
              )[0].real
          )
      return rst
  
imports: import copy
  from collections.abc import Iterable, Mapping
  import numpy
  import scipy.sparse
  import scipy.sparse.linalg
  from ..utils import version
  from ..None import backend, batch, convert, function, ndarray, subgraph, utils
  from .._ffi.function import _init_api
  from ..base import dgl_warning, DGLError, EID, NID
  from ..frame import Frame
  from ..heterograph import DGLGraph
  from ..heterograph_index import create_heterograph_from_relations, create_metagraph_index
  from ..partition import metis_partition, metis_partition_assignment, partition_graph_with_halo
  from ..sampling.neighbor import sample_neighbors
label_desc: Use image node_id 15 for calling a global function with example usage: laplacian_lambda_max(g) and returns: rst