code: def main(args):
      if len(args) != 3:
          print("Expected: {export_path} {ModuleName}")
          print("Allowed ModuleNames:", MODULE_CTORS.keys())
          return 1
  
      _, export_path, module_name = args
      module_ctor, version = MODULE_CTORS.get(module_name)
      if not module_ctor:
          print(
              "Expected ModuleName to be one of:", MODULE_CTORS.keys()
          )
          return 2
      os.makedirs(export_path)
  
      tf_module = module_ctor()
      if version == 2:
          options = save_options.SaveOptions(save_debug_info=True)
          saved_model.save(tf_module, export_path, options=options)
      else:
          builder = saved_model.builder.SavedModelBuilder(export_path)
          builder.add_meta_graph_and_variables(tf_module, ["serve"])
          builder.save()
  
imports: import os
  from absl import app
  from tensorflow.python.client import session
  from tensorflow.python.compat import v2_compat
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.module import module
  from tensorflow.python.ops import io_ops
  from tensorflow.python.ops import lookup_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.saved_model import save_options
  from tensorflow.python.saved_model import saved_model
  from tensorflow.python.trackable import asset
label_desc: Use image node_id 2 for calling a global function with example usage: main(args) and returns: int, int