code: def testAirflowDagRunner(
      self, mock_airflow_dag_class, mock_airflow_component_class
  ):
      mock_airflow_dag_class.return_value = "DAG"
      mock_airflow_component_a = mock.Mock()
      mock_airflow_component_b = mock.Mock()
      mock_airflow_component_c = mock.Mock()
      mock_airflow_component_d = mock.Mock()
      mock_airflow_component_e = mock.Mock()
      mock_airflow_component_class.side_effect = [
          mock_airflow_component_a,
          mock_airflow_component_b,
          mock_airflow_component_c,
          mock_airflow_component_d,
          mock_airflow_component_e,
      ]
  
      airflow_config = {
          "schedule_interval": "* * * * *",
          "start_date": datetime.datetime(2019, 1, 1),
      }
      component_a = _FakeComponent(
          _FakeComponentSpecA(output=types.Channel(type=_ArtifactTypeA))
      )
      component_b = _FakeComponent(
          _FakeComponentSpecB(
              a=component_a.outputs["output"],
              output=types.Channel(type=_ArtifactTypeB),
          )
      )
      component_c = _FakeComponent(
          _FakeComponentSpecC(
              a=component_a.outputs["output"],
              b=component_b.outputs["output"],
              output=types.Channel(type=_ArtifactTypeC),
          )
      )
      component_d = _FakeComponent(
          _FakeComponentSpecD(
              b=component_b.outputs["output"],
              c=component_c.outputs["output"],
              output=types.Channel(type=_ArtifactTypeD),
          )
      )
      component_e = _FakeComponent(
          _FakeComponentSpecE(
              a=component_a.outputs["output"],
              b=component_b.outputs["output"],
              d=component_d.outputs["output"],
              output=types.Channel(type=_ArtifactTypeE),
          )
      )
  
      test_pipeline = pipeline.Pipeline(
          pipeline_name="x",
          pipeline_root="y",
          metadata_connection_config=None,
          components=[
              component_d,
              component_c,
              component_a,
              component_b,
              component_e,
          ],
      )
      runner = airflow_dag_runner.AirflowDagRunner(
          airflow_dag_runner.AirflowPipelineConfig(
              airflow_dag_config=airflow_config
          )
      )
      runner.run(test_pipeline)
  
      mock_airflow_component_a.set_upstream.assert_not_called()
      mock_airflow_component_b.set_upstream.assert_has_calls(
          [mock.call(mock_airflow_component_a)]
      )
      mock_airflow_component_c.set_upstream.assert_has_calls(
          [
              mock.call(mock_airflow_component_a),
              mock.call(mock_airflow_component_b),
          ],
          any_order=True,
      )
      mock_airflow_component_d.set_upstream.assert_has_calls(
          [
              mock.call(mock_airflow_component_b),
              mock.call(mock_airflow_component_c),
          ],
          any_order=True,
      )
      mock_airflow_component_e.set_upstream.assert_has_calls(
          [
              mock.call(mock_airflow_component_a),
              mock.call(mock_airflow_component_b),
              mock.call(mock_airflow_component_d),
          ],
          any_order=True,
      )
  
imports: import datetime
  from unittest import mock
  import tensorflow
  from tfx import types
  from tfx.dsl.components.base import base_component
  from tfx.dsl.components.base import base_executor
  from tfx.dsl.components.base import executor_spec
  from tfx.orchestration import pipeline
  from tfx.orchestration.airflow import airflow_dag_runner
  from tfx.orchestration.data_types import RuntimeParameter
  from tfx.types import component_spec
label_desc: Use image node_id 1 for calling the AirflowDagRunnerTest obj's underlying member method code with example usage: obj.testAirflowDagRunner(mock_airflow_dag_class, mock_airflow_component_class) without return types