code: def G2():
      # Now we shift all the weights by -10.
      # Should not affect optimal arborescence, but does affect optimal branching.
      Garr = G_array.copy()
      Garr[np.nonzero(Garr)] -= 10
      G = nx.from_numpy_array(Garr, create_using=nx.MultiDiGraph)
      return G
  
imports: import math
  from operator import itemgetter
  import pytest
  import networkx
  from networkx.algorithms.tree import branchings, recognition
label_desc: Use image node_id 2 for calling a global function with example usage: G2() and returns: G