class_docstr: TFX runner on Kubernetes.
class_docstr_tok: ["TFX","runner","on","Kubernetes","."]
docstr: Initializes KubernetesDagRunner as a TFX orchestrator.
  
  Args:
    config: Optional pipeline config for customizing the launching of each
      component. Defaults to pipeline config that supports
      InProcessComponentLauncher and KubernetesComponentLauncher.
docstr_tok: ["Initializes","KubernetesDagRunner","as","a","TFX","orchestrator",".","Args",":","config",":","Optional","pipeline","config","for","customizing","the","launching","of","each","component",".","Defaults","to","pipeline","config","that","supports","InProcessComponentLauncher","and","KubernetesComponentLauncher","."]
code: def __init__(
      self, config: Optional[KubernetesDagRunnerConfig] = None
  ):
      """Initializes KubernetesDagRunner as a TFX orchestrator.
  
      Args:
        config: Optional pipeline config for customizing the launching of each
          component. Defaults to pipeline config that supports
          InProcessComponentLauncher and KubernetesComponentLauncher.
      """
      if config is None:
          config = KubernetesDagRunnerConfig()
      super().__init__(config)
  
imports: import datetime
  import json
  from typing import List, Optional, Type
  from absl import logging
  from tfx.dsl.component.experimental import container_component
  from tfx.dsl.components.base import base_node
  from tfx.orchestration import data_types
  from tfx.orchestration import metadata
  from tfx.orchestration import pipeline
  from tfx.orchestration import tfx_runner
  from tfx.orchestration.config import base_component_config
  from tfx.orchestration.config import config_utils
  from tfx.orchestration.config import pipeline_config
  from tfx.orchestration.experimental.kubernetes import kubernetes_remote_runner
  from tfx.orchestration.experimental.kubernetes import node_wrapper
  from tfx.orchestration.launcher import base_component_launcher
  from tfx.orchestration.launcher import in_process_component_launcher
  from tfx.orchestration.launcher import kubernetes_component_launcher
  from tfx.utils import json_utils
  from tfx.utils import kube_utils
  from tfx.utils import name_utils
  from google.protobuf import json_format
  from ml_metadata.proto import metadata_store_pb2
label_desc: Use image node_id 1 to create a new KubernetesDagRunner object from inherited base classes: tfx_runner with example: obj = KubernetesDagRunner(config)