class_docstr: Base runner class for TFX.
  
  This is the base class for every TFX runner.
class_docstr_tok: ["Base","runner","class","for","TFX",".","This","is","the","base","class","for","every","TFX","runner","."]
docstr: Runs a TFX pipeline on a specific platform.
  
  Args:
    pipeline: a pipeline.Pipeline instance representing a pipeline definition.
    run_options: an Optional pipeline.RunOptions object. See
      the class definition pipeline.RunOptions for details. If None,
      runs the full pipeline.
    **kwargs: extra orchestrator backend-specific keyword arguments.
  
  Returns:
    Optional platform-specific object.
docstr_tok: ["Runs","a","TFX","pipeline","on","a","specific","platform",".","Args",":","pipeline",":","a","pipeline.Pipeline","instance","representing","a","pipeline","definition",".","run_options",":","an","Optional","pipeline.RunOptions","object",".","See","the","class","definition","pipeline.RunOptions","for","details",".","If","None",",","runs","the","full","pipeline",".","*","*","kwargs",":","extra","orchestrator","backend-specific","keyword","arguments",".","Returns",":","Optional","platform-specific","object","."]
code: def run(
      self,
      pipeline: pipeline_py.Pipeline,
      run_options: Optional[pipeline_py.RunOptions] = None,
      **kwargs: Any,
  ) -> Optional[Any]:
      """Runs a TFX pipeline on a specific platform.
  
      Args:
        pipeline: a pipeline.Pipeline instance representing a pipeline definition.
        run_options: an Optional pipeline.RunOptions object. See
          the class definition pipeline.RunOptions for details. If None,
          runs the full pipeline.
        **kwargs: extra orchestrator backend-specific keyword arguments.
  
      Returns:
        Optional platform-specific object.
      """
      pass
  
file_path: tfx/tfx/orchestration/portable/tfx_runner.py
imports: import abc
  from typing import Any, Optional
  from tfx.dsl.compiler import compiler
  from tfx.dsl.components.base import base_component
  from tfx.orchestration import pipeline
  from tfx.proto.orchestration import pipeline_pb2
  from tfx.utils import doc_controls
label_desc: Use image node_id 1 for calling the TfxRunner obj's underlying member method code with example usage: obj.run(pipeline, run_options) without return types