code: def create_vocab_indices_map(c2_prepared, 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(
              # Skip index 0 as it is reserved for unkwon tokens
              # in Caffe2's index implementation
              np.array(vocab[1:], dtype=str),
              init_net,
              c2_prepared.workspace,
              feat_name + "_index",
          )
      return vocab_indices
  
file_path: pytext/pytext/utils/onnx.py
imports: import caffe2.python.predictor.predictor_exporter
  import numpy
  import torch
  from caffe2.python import core, workspace
  from caffe2.python.onnx import backend
  from torch.onnx import ExportTypes, OperatorExportTypes
label_desc: Use image node_id 4 for calling a global function with example usage: create_vocab_indices_map(c2_prepared, init_net, vocab_map) and returns: vocab_indices