code: def test_creation_and_hydration(run_data):
      rd, metrics, params, tags = run_data
      _check(rd, metrics, params, tags)
      as_dict = {
          "metrics": {m.key: m.value for m in metrics},
          "params": {p.key: p.value for p in params},
          "tags": {t.key: t.value for t in tags},
      }
      assert dict(rd) == as_dict
      proto = rd.to_proto()
      rd2 = RunData.from_proto(proto)
      _check(rd2, metrics, params, tags)
  
imports: from mlflow.entities import RunData
label_desc: Use image node_id 5 for calling a global function with example usage: test_creation_and_hydration(run_data) without return types