code: def test_nnlda():
      torch.manual_seed(42)
      # https://github.com/diffqc/dqc/blob/742eb2576418464609f942def4fb7c3bbdc0cd82/dqc/test/test_xc.py#L15
      n = 2
      model = dummymodel()
      k = NNLDA(model)
      densinfo = ValGrad(
          value=torch.rand((n,), dtype=torch.float32).requires_grad_()
      )
      output = k.get_edensityxc(densinfo).detach()
      expected_output = torch.tensor([0.3386, 0.0177])
      torch.testing.assert_close(
          output, expected_output, atol=1e-4, rtol=0
      )
  
label_desc: Use image node_id 2 for calling a global function with example usage: test_nnlda() without return types