code: def experimental_convert_saved_model_to_mlir(
      saved_model_path, exported_names, show_debug_info
  ):
      return ExperimentalConvertSavedModelToMlir(
          str(saved_model_path).encode("utf-8"),
          str(exported_names).encode("utf-8"),
          show_debug_info,
      )
  
file_path: tensorflow-upstream/tensorflow/python/pywrap_mlir.py
imports: from tensorflow.python import pywrap_tensorflow
  from tensorflow.python.eager import context
  from tensorflow.python._pywrap_mlir import *
label_desc: Use image node_id 3 for calling a global function with example usage: experimental_convert_saved_model_to_mlir(saved_model_path, exported_names, show_debug_info) and returns: ExperimentalConvertSavedModelToMlir