code: def test_bro():
      batch = torch.tensor([0, 0, 0, 0, 1, 1, 1, 2, 2])
  
      g1 = torch.tensor(
          [
              [0.2, 0.2, 0.2, 0.2],
              [0.0, 0.2, 0.2, 0.2],
              [0.2, 0.0, 0.2, 0.2],
              [0.2, 0.2, 0.0, 0.2],
          ]
      )
  
      g2 = torch.tensor(
          [
              [0.2, 0.2, 0.2, 0.2],
              [0.0, 0.2, 0.2, 0.2],
              [0.2, 0.0, 0.2, 0.2],
          ]
      )
  
      g3 = torch.tensor(
          [
              [0.2, 0.2, 0.2, 0.2],
              [0.2, 0.0, 0.2, 0.2],
          ]
      )
  
      s = 0.0
      for g in [g1, g2, g3]:
          s += torch.norm(g @ g.t() - torch.eye(g.shape[0]), p=2)
  
      assert torch.isclose(
          s / 3.0, bro(torch.cat([g1, g2, g3], dim=0), batch)
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_bro() without return types