code: def add_feats_numericalize_ops(
      init_net, predict_net, vocab_map, input_names
  ):
      (
          init_net,
          final_predict_net,
          final_input_names,
      ) = get_numericalize_net(
          init_net, predict_net, vocab_map, input_names
      )
  
      create_context(init_net)
      init_net = init_net.Proto()
      final_predict_net.Proto().op.extend(predict_net.op)
      predict_net = final_predict_net.Proto()
      return (init_net, predict_net, final_input_names)
  
file_path: pytext/pytext/utils/mobile_onnx.py
imports: import itertools
  import numpy
  import onnx
  import torch
  from caffe2.python import core, utils, workspace
  from caffe2.python.onnx import backend
  from pytext.utils.onnx import convert_caffe2_blob_name
label_desc: Use image node_id 3 for calling a global function with example usage: add_feats_numericalize_ops(init_net, predict_net, vocab_map, input_names) and returns: init_net,  predict_net,  final_input_names