code: def run_pass_pipeline(mlir_txt, pass_pipeline, show_debug_info=False):
      """Runs a pipeline over input module.
  
      Args:
        mlir_txt: Textual representation of the MLIR module.
        pass_pipeline: Pass pipeline to run on module.
        show_debug_info: Whether to include locations in the emitted textual form.
  
      Returns:
        A textual representation of the MLIR module corresponding to the
        transformed module.
      """
      return pywrap_mlir.experimental_run_pass_pipeline(
          mlir_txt, pass_pipeline, show_debug_info
      )
  
file_path: tensorflow/tensorflow/python/compiler/mlir/mlir.py
imports: from tensorflow.python import pywrap_mlir
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 5 for calling a global function with example usage: run_pass_pipeline(mlir_txt, pass_pipeline, show_debug_info) and returns: pywrap_mlir