code: def import_graphdef(
      graphdef,
      pass_pipeline,
      show_debug_info,
      input_names=None,
      input_data_types=None,
      input_data_shapes=None,
      output_names=[],
  ):
      if input_names is not None:
          return ImportGraphDef(
              str(graphdef).encode("utf-8"),
              pass_pipeline.encode("utf-8"),
              show_debug_info,
              ",".join(input_names).encode("utf-8"),
              ",".join(input_data_types).encode("utf-8"),
              ":".join(input_data_shapes).encode("utf-8"),
              ",".join(output_names).encode("utf-8"),
          )
      return ImportGraphDef(
          str(graphdef).encode("utf-8"),
          pass_pipeline.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 1 for calling a global function with example usage: import_graphdef(graphdef, pass_pipeline, show_debug_info, input_names, input_data_types, input_data_shapes, output_names) and returns: ImportGraphDef, ImportGraphDef