code: def experimental_convert_saved_model_v1_to_mlir(
      saved_model_path,
      exported_names,
      tags,
      lift_variables,
      include_variables_in_initializers,
      upgrade_legacy,
      show_debug_info,
  ):
      return ExperimentalConvertSavedModelV1ToMlir(
          str(saved_model_path).encode("utf-8"),
          str(exported_names).encode("utf-8"),
          str(tags).encode("utf-8"),
          lift_variables,
          include_variables_in_initializers,
          upgrade_legacy,
          show_debug_info,
      )
  
file_path: tensorflow/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 5 for calling a global function with example usage: experimental_convert_saved_model_v1_to_mlir(saved_model_path, exported_names, tags, lift_variables, include_variables_in_initializers, upgrade_legacy, show_debug_info) and returns: ExperimentalConvertSavedModelV1ToMlir