code: def _get_list_bigqueryml_models(self, api, dataset_name):
      r = (
          api.models()
          .list(projectId=self._GCP_PROJECT_ID, datasetId=dataset_name)
          .execute()
      )
      if r:
          return [m["modelReference"]["modelId"] for m in r["models"]]
      else:
          return []
  
imports: import os
  import absl
  from googleapiclient import discovery
  from googleapiclient import errors
  import tensorflow
  from tfx import v1
  from tfx.components.pusher.component import Pusher
  from tfx.components.trainer.component import Trainer
  from tfx.dsl.components.base import executor_spec
  from tfx.dsl.components.common import importer
  from tfx.dsl.io import fileio
  from tfx.extensions.google_cloud_ai_platform import constants
  from tfx.extensions.google_cloud_ai_platform import runner
  from tfx.extensions.google_cloud_ai_platform.pusher import executor
  from tfx.extensions.google_cloud_ai_platform.trainer import executor
  from tfx.extensions.google_cloud_ai_platform.tuner import component
  from tfx.extensions.google_cloud_ai_platform.tuner import executor
  from tfx.extensions.google_cloud_big_query.pusher import executor
  from tfx.orchestration import test_utils
  from tfx.orchestration.kubeflow import test_utils
  from tfx.proto import trainer_pb2
  from tfx.proto import tuner_pb2
  from tfx.types import standard_artifacts
  from tfx.utils import path_utils
  from tfx.utils import telemetry_utils
label_desc: Use image node_id 13 for calling the KubeflowGCPIntegrationTest obj's underlying member method code with example usage: obj._get_list_bigqueryml_models(api, dataset_name) and returns: unknown, list