code: def test_scf():
      torch.manual_seed(42)
      nnmodel = (
          torch.nn.Sequential(
              torch.nn.Linear(2, 10),
              torch.nn.Softplus(),
              torch.nn.Linear(10, 1, bias=False),
          )
      ).to(torch.double)
      hybridxc = HybridXC("lda_x", nnmodel, aweight0=0.0)
      e_type = "ae"
      true_val = "0.09194410469"
      systems = [
          {
              "moldesc": "Li 1.5070 0 0; H -1.5070 0 0",
              "basis": "6-311++G(3df,3pd)",
          },
          {
              "moldesc": "Li 0 0 0",
              "basis": "6-311++G(3df,3pd)",
              "spin": 1,
          },
          {
              "moldesc": "H 0 0 0",
              "basis": "6-311++G(3df,3pd)",
              "spin": 1,
          },
      ]
      entry = DFTEntry.create(e_type, true_val, systems)
      evl = XCNNSCF(hybridxc, entry)
      system = DFTSystem(systems[1])
      run = evl.run(system)
      output = run.energy()
      expected_output = torch.tensor(-7.1914, dtype=torch.float64)
      torch.testing.assert_close(
          output, expected_output, atol=1e-4, rtol=0
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_scf() without return types