class_docstr: Tfx runner on Beam.
class_docstr_tok: ["Tfx","runner","on","Beam","."]
docstr: Initializes BeamDagRunner as a TFX orchestrator.
  
  Args:
    beam_orchestrator_args: beam args for the beam orchestrator. Note that
      this is different from the beam_pipeline_args within
      additional_pipeline_args, which is for beam pipelines in components.
    config: Optional pipeline config for customizing the launching of each
      component. Defaults to pipeline config that supports
      InProcessComponentLauncher and DockerComponentLauncher.
docstr_tok: ["Initializes","BeamDagRunner","as","a","TFX","orchestrator",".","Args",":","beam_orchestrator_args",":","beam","args","for","the","beam","orchestrator",".","Note","that","this","is","different","from","the","beam_pipeline_args","within","additional_pipeline_args",",","which","is","for","beam","pipelines","in","components",".","config",":","Optional","pipeline","config","for","customizing","the","launching","of","each","component",".","Defaults","to","pipeline","config","that","supports","InProcessComponentLauncher","and","DockerComponentLauncher","."]
code: def __init__(
      self,
      beam_orchestrator_args: Optional[List[str]] = None,
      config: Optional[pipeline_config.PipelineConfig] = None,
  ):
      """Initializes BeamDagRunner as a TFX orchestrator.
  
      Args:
        beam_orchestrator_args: beam args for the beam orchestrator. Note that
          this is different from the beam_pipeline_args within
          additional_pipeline_args, which is for beam pipelines in components.
        config: Optional pipeline config for customizing the launching of each
          component. Defaults to pipeline config that supports
          InProcessComponentLauncher and DockerComponentLauncher.
      """
      if config is None:
          config = pipeline_config.PipelineConfig(
              supported_launcher_classes=[
                  in_process_component_launcher.InProcessComponentLauncher,
                  docker_component_launcher.DockerComponentLauncher,
              ],
          )
      super().__init__(config)
      self._beam_orchestrator_args = beam_orchestrator_args
  
imports: import datetime
  from typing import Any, Iterable, List, Optional, Type
  import absl
  import apache_beam
  from tfx.dsl.components.base import base_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.launcher import base_component_launcher
  from tfx.orchestration.launcher import docker_component_launcher
  from tfx.orchestration.launcher import in_process_component_launcher
  from tfx.utils import telemetry_utils
label_desc: Use image node_id 1 to create a new BeamDagRunner object from inherited base classes: tfx_runner with example: obj = BeamDagRunner(beam_orchestrator_args, config)