code: def test_Edmond_kind():
      G = nx.MultiGraph()
  
      edgelist = [
          (0, 1, [("weight", 5), ("otherattr", 1), ("otherattr2", 3)]),
          (0, 2, [("weight", 5), ("otherattr", 2), ("otherattr2", 2)]),
          (1, 2, [("weight", 6), ("otherattr", 3), ("otherattr2", 1)]),
      ]
      G.add_edges_from(
          edgelist * 2
      )  # Make sure we have duplicate edge paths
      ed = branchings.Edmonds(G)
      with pytest.raises(
          nx.NetworkXException, match="Unknown value for `kind`."
      ):
          ed.find_optimum(kind="lol", preserve_attrs=True)
  
imports: import math
  from operator import itemgetter
  import pytest
  import networkx
  from networkx.algorithms.tree import branchings, recognition
label_desc: Use image node_id 31 for calling a global function with example usage: test_Edmond_kind() without return types