code: def test_get_metrics():
      """This is to test the get metrics function with respect to different selection method"""
      scores1 = {
          "name": "test1",
          "metrics": ["keep positive", "keep absolute"],
          "values": dict(),
      }
      scores2 = {
          "name": "test2",
          "metrics": ["keep positive", "keep negative"],
          "values": dict(),
      }
      benchmarks = {"test1": scores1, "test2": scores2}
  
      expected_metrics1 = set(["keep positive"])
      expected_metrics2 = set(
          ["keep positive", "keep negative", "keep absolute"]
      )
  
      assert (
          set(
              shap.benchmark.get_metrics(
                  benchmarks, lambda x, y: x.intersection(y)
              )
          )
          == expected_metrics1
      )
      assert (
          set(
              shap.benchmark.get_metrics(
                  benchmarks, lambda x, y: x.union(y)
              )
          )
          == expected_metrics2
      )
  
imports: import numpy
  import shap
label_desc: Use image node_id 4 for calling a global function with example usage: test_get_metrics() without return types