code: def setUp(self):
      super().setUp()
  
      # Transformed Example artifacts for testing.
      self.transformed_examples_importer = importer.Importer(
          source_uri=os.path.join(
              self._test_data_dir, "transform", "transformed_examples"
          ),
          artifact_type=standard_artifacts.Examples,
          reimport=True,
          properties={"split_names": '["train", "eval"]'},
      ).with_id("transformed_examples")
  
      # Schema artifact for testing.
      self.schema_importer = importer.Importer(
          source_uri=os.path.join(self._test_data_dir, "schema_gen"),
          artifact_type=standard_artifacts.Schema,
          reimport=True,
      ).with_id("schema")
  
      # TransformGraph artifact for testing.
      self.transform_graph_importer = importer.Importer(
          source_uri=os.path.join(
              self._test_data_dir, "transform", "transform_graph"
          ),
          artifact_type=standard_artifacts.TransformGraph,
          reimport=True,
      ).with_id("transform_graph")
  
      # Model artifact for testing.
      self.model_1_importer = importer.Importer(
          source_uri=os.path.join(
              self._test_data_dir, "trainer", "previous"
          ),
          artifact_type=standard_artifacts.Model,
          reimport=True,
      ).with_id("model_1")
  
      self.model_2_importer = importer.Importer(
          source_uri=os.path.join(
              self._test_data_dir, "trainer", "current"
          ),
          artifact_type=standard_artifacts.Model,
          reimport=True,
      ).with_id("model_2")
  
      # ModelBlessing artifact for testing.
      self.model_blessing_1_importer = importer.Importer(
          source_uri=os.path.join(
              self._test_data_dir, "model_validator", "blessed"
          ),
          artifact_type=standard_artifacts.ModelBlessing,
          reimport=True,
          custom_properties={"blessed": 1},
      ).with_id("model_blessing_1")
  
      self.model_blessing_2_importer = importer.Importer(
          source_uri=os.path.join(
              self._test_data_dir, "model_validator", "blessed"
          ),
          artifact_type=standard_artifacts.ModelBlessing,
          reimport=True,
          custom_properties={"blessed": 1},
      ).with_id("model_blessing_2")
  
      ### Test data and modules for native Keras trainer and tuner.
      self._penguin_tuner_module = os.path.join(
          self._MODULE_ROOT, "tuner_module.py"
      )
      self.penguin_examples_importer = importer.Importer(
          source_uri=os.path.join(
              self._test_data_dir, "penguin", "data"
          ),
          artifact_type=standard_artifacts.Examples,
          reimport=True,
          properties={"split_names": '["train", "eval"]'},
      ).with_id("penguin_examples")
      self.penguin_schema_importer = importer.Importer(
          source_uri=os.path.join(
              self._test_data_dir, "penguin", "schema"
          ),
          artifact_type=standard_artifacts.Schema,
          reimport=True,
      ).with_id("penguin_schema")
  
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 1 for calling the KubeflowGCPIntegrationTest obj's underlying member method code with example usage: obj.setUp() without return types