code: def run_tvm(lib):
      from tvm.contrib import graph_executor
  
      rt_mod = graph_executor.GraphModule(lib["default"](tvm.cpu(0)))
      rt_mod.set_input("input", data)
      rt_mod.run()
      tvm_res = rt_mod.get_output(0).numpy()
      tvm_pred = np.squeeze(tvm_res).argsort()[-5:][::-1]
      return tvm_pred, rt_mod
  
file_path: tvm/gallery/how_to/deploy_models/deploy_prequantized_tflite.py
imports: import os
  import numpy
  import tflite
  import tvm
  from tvm import relay
  from tvm.contrib.download import download_testdata
label_desc: Use image node_id 4 for calling a global function with example usage: run_tvm(lib) and returns: tvm_pred,  rt_mod