code: def test_mli_visualize_interop():
      data = synthetic_classification()
      lr = LogisticRegression()
  
      lr.fit(data["train"]["X"], data["train"]["y"])
  
      global_exp = lr.explain_global()
      assert "mli" in global_exp.data(-1)
      global_overall_viz = global_exp.visualize()
      assert global_overall_viz is not None
      global_specific_viz = global_exp.visualize(0)
      assert global_specific_viz is not None
      mli_global_specific_viz = global_exp.visualize(("mli", 0))
      assert mli_global_specific_viz is not None
  
      local_exp = lr.explain_local(
          data["test"]["X"].head(), data["test"]["y"].head()
      )
      assert "mli" in local_exp.data(-1)
      local_specific_viz = local_exp.visualize(0)
      assert local_specific_viz is not None
      mli_local_specific_viz = local_exp.visualize(("mli", 0))
      assert mli_local_specific_viz is not None
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_mli_visualize_interop() without return types