code: def create_vocab_indices_map(init_net, vocab_map):
      vocab_indices = {}
      for feat_name, vocab in vocab_map.items():
          assert len(vocab) > 1
          vocab_indices[feat_name] = create_vocab_index(
              np.array(vocab, dtype=str)[1:],
              init_net,
              workspace,
              feat_name + "_index",
          )
      return vocab_indices
  
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 5 for calling a global function with example usage: create_vocab_indices_map(init_net, vocab_map) and returns: vocab_indices