class_docstr: Kubeflow pipelines RuntimeConfig builder.
class_docstr_tok: ["Kubeflow","pipelines","RuntimeConfig","builder","."]
docstr: Build a RuntimeConfig proto.
docstr_tok: ["Build","a","RuntimeConfig","proto","."]
code: def build(self) -> pipeline_pb2.PipelineJob.RuntimeConfig:
      """Build a RuntimeConfig proto."""
      return pipeline_pb2.PipelineJob.RuntimeConfig(
          gcs_output_directory=self._pipeline_root,
          parameters={
              k: compiler_utils.get_kubeflow_value(v)
              for k, v in self._parameter_values.items()
          },
      )
  
imports: import random
  import re
  import string
  import typing
  from typing import Any, Dict, List, Mapping, Optional, Union
  from absl import logging
  from kfp.pipeline_spec import pipeline_spec_pb2
  from tfx.dsl.components.base import base_node
  from tfx.dsl.placeholder import placeholder
  from tfx.orchestration import data_types
  from tfx.orchestration import pipeline
  from tfx.orchestration.kubeflow import utils
  from tfx.orchestration.kubeflow.v2 import compiler_utils
  from tfx.orchestration.kubeflow.v2 import parameter_utils
  from tfx.orchestration.kubeflow.v2 import step_builder
  from tfx.types import channel_utils
  from google.protobuf import json_format
label_desc: Use image node_id 2 for calling the RuntimeConfigBuilder obj's underlying member method code with example usage: obj.build() and returns: pipeline_pb2