code: def testVolumeMountingPipelineOperatorFuncs(self):
      mount_volume_op = onprem.mount_pvc(
          "my-persistent-volume-claim",
          "my-volume-name",
          "/mnt/volume-mount-path",
      )
      config = kubeflow_dag_runner.KubeflowDagRunnerConfig(
          pipeline_operator_funcs=[mount_volume_op]
      )
  
      kubeflow_dag_runner.KubeflowDagRunner(config=config).run(
          _two_step_pipeline()
      )
      file_path = "two_step_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)
  
          container_templates = [
              c
              for c in pipeline["spec"]["templates"]
              if "container" in c
          ]
          self.assertEqual(2, len(container_templates))
  
          volumes = [
              {
                  "name": "my-volume-name",
                  "persistentVolumeClaim": {
                      "claimName": "my-persistent-volume-claim"
                  },
              }
          ]
  
          # Check that the PVC is specified for kfp<=0.1.31.1.
          if "volumes" in pipeline["spec"]:
              self.assertEqual(volumes, pipeline["spec"]["volumes"])
  
          for template in container_templates:
              # Check that each container has the volume mounted.
              self.assertEqual(
                  [
                      {
                          "name": "my-volume-name",
                          "mountPath": "/mnt/volume-mount-path",
                      }
                  ],
                  template["container"]["volumeMounts"],
              )
  
              # Check that each template has the PVC specified for kfp>=0.1.31.2.
              if "volumes" in template:
                  self.assertEqual(volumes, template["volumes"])
  
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 6 for calling the KubeflowDagRunnerTest obj's underlying member method code with example usage: obj.testVolumeMountingPipelineOperatorFuncs() without return types