code: def test(a_node, pp):
      ######################################################################
      # Now look for kmeans_prostate_model_name using the one-model API and find_compatible_frames, and check it
      model = a_node.models(
          key="kmeans_prostate", find_compatible_frames=True
      )
      found_kmeans = False
      h2o.H2O.verboseprint(
          "k-means model with find_compatible_frames output: "
      )
      h2o.H2O.verboseprint(
          "/Models/",
          "kmeans_prostate",
          "?find_compatible_frames=true: ",
          repr(model),
      )
      h2o_test_utils.assertKeysExist(
          model["models"][0], "", ["compatible_frames"]
      )
  
      # CAPSULE is numeric in prostate_regression and categorical in prostate_binomial:
      assert (
          "prostate_regression"
          in model["models"][0]["compatible_frames"]
      ), (
          "FAIL: Failed to find "
          + "prostate_regression"
          + " in compatible_frames list."
      )
      assert (
          "prostate_binomial"
          not in model["models"][0]["compatible_frames"]
      ), (
          "FAIL: Incorrectly found "
          + "prostate_binomial"
          + " in compatible_frames list."
      )
  
      ######################################################################
      # Now look for 'prostate_binomial' using the one-frame API and find_compatible_models, and check it
      result = a_node.frames(
          key="prostate_binomial",
          find_compatible_models=True,
          row_count=5,
      )
      frames = result["frames"]
      frames_dict = h2o_test_utils.list_to_dict(frames, "frame_id/name")
      assert (
          "prostate_binomial" in frames_dict
      ), "FAIL: Failed to find prostate.hex in Frames list."
  
      compatible_models = result["compatible_models"]
      models_dict = h2o_test_utils.list_to_dict(
          compatible_models, "model_id/name"
      )
      assert "deeplearning_prostate_binomial" in models_dict, (
          "FAIL: Failed to find "
          + "deeplearning_prostate_binomial"
          + " in compatible models list: "
          + repr(result)
      )
  
      assert (
          "deeplearning_prostate_binomial"
          in frames[0]["compatible_models"]
      ), "FAIL: failed to find deeplearning_prostate_binomial in compatible_models for prostate_binomial."
      assert (
          "deeplearning_prostate_regression"
          not in frames[0]["compatible_models"]
      ), "FAIL: Incorrectly found deeplearning_prostate_regression in compatible_models for prostate_binomial."
      assert (
          "kmeans_prostate" not in frames[0]["compatible_models"]
      ), "FAIL: Incorrectly found kmeans_prostate in compatible_models for prostate_binomial."
      h2o.H2O.verboseprint(
          "/Frames/prosate.hex?find_compatible_models=true: ",
          repr(result),
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: test(a_node, pp) without return types