code: def test_multiatom():
      inputs = "deepchem/models/tests/assets/test_beh2.yaml"
      k = DFTYamlLoader()
      data = k.create_dataset(inputs)
      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)
      entry = data.X[0]
      evl = XCNNSCF(hybridxc, entry)
      qcs = []
      for system in entry.get_systems():
          qcs.append(evl.run(system))
      val = entry.get_val(qcs)
      expected_val = np.array([0.19325158])
      assert np.allclose(val, expected_val)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_multiatom() without return types