code: def testContainerComponent(self):
      kubeflow_dag_runner.KubeflowDagRunner().run(
          _container_component_pipeline()
      )
      file_path = os.path.join(
          self.tmp_dir, "container_component_pipeline.tar.gz"
      )
      self.assertTrue(fileio.exists(file_path))
  
      with tarfile.TarFile.open(file_path).extractfile(
          "pipeline.yaml"
      ) as pipeline_file:
          self.assertIsNotNone(pipeline_file)
          pipeline = yaml.safe_load(pipeline_file)
          containers = [
              c
              for c in pipeline["spec"]["templates"]
              if "container" in c
          ]
          self.assertLen(containers, 1)
          component_args = containers[0]["container"]["args"]
          self.assertIn("--node_id", component_args)
  
imports: import json
  import os
  import tarfile
  from typing import List
  from kfp import onprem
  import tensorflow
  from tfx.components.statistics_gen import component
  from tfx.dsl.component.experimental import executor_specs
  from tfx.dsl.component.experimental.annotations import Parameter
  from tfx.dsl.component.experimental.decorators import component
  from tfx.dsl.components.base import base_component
  from tfx.dsl.io import fileio
  from tfx.extensions.google_cloud_big_query.example_gen import component
  from tfx.orchestration import data_types
  from tfx.orchestration import pipeline
  from tfx.orchestration.kubeflow import kubeflow_dag_runner
  from tfx.orchestration.kubeflow.decorators import FinalStatusStr
  from tfx.proto import example_gen_pb2
  from tfx.types import component_spec
  from tfx.utils import telemetry_utils
  from tfx.utils import test_case_utils
  import yaml
  from ml_metadata.proto import metadata_store_pb2
label_desc: Use image node_id 7 for calling the KubeflowDagRunnerTest obj's underlying member method code with example usage: obj.testContainerComponent() without return types