code: def test_model(pass_name):
      args = {"a": mx.nd.ones((3, 2)), "b": mx.nd.ones((3, 2))}
      # execute in MXNet
      print("-------------------------------")
      print("Testing regular MXNet execution")
      inputs = [a, b]
      sym_block = nn.SymbolBlock(sym, inputs)
      sym_block.initialize()
      out = sym_block(mx.nd.ones((3, 2)), mx.nd.ones((3, 2)))
      print(out)
  
      # Gluon optimize_for
      print("-------------------------------")
      print(
          f'Testing pass "{pass_name}" Gluon Hybridize with shapes/types without inference'
      )
      inputs = [a, b]
      sym_block2 = nn.SymbolBlock(sym, inputs)
      sym_block2.initialize()
      sym_block2.optimize_for(
          mx.nd.ones((3, 2)), mx.nd.ones((3, 2)), backend=pass_name
      )
      sym_block2.export("modified")
  
imports: import os, ctypes
  import mxnet
  from mxnet.gluon import nn
  from mxnet import nd
  from mxnet.base import _LIB, check_call, mx_uint, c_str, c_str_array, SymbolHandle
label_desc: Use image node_id 1 for calling a global function with example usage: test_model(pass_name) without return types