code: def load_wv_vocab(file):
      """Load tokens from word vector file.
  
      Only tokens are loaded. Vectors are not loaded at this time for space efficiency.
  
      Args:
          file (str): path of pretrained word vector file.
  
      Returns:
          set: a set of tokens (str) contained in the word vector file.
      """
      vocab = set()
      with open(file) as f:
          for line in f:
              elems = line.split()
              token = normalize_text(
                  "".join(elems[0:-wv_dim])
              )  # a token may contain space
              vocab.add(token)
      return vocab
  
imports: import re
  import json
  import spacy
  import msgpack
  import unicodedata
  import numpy
  import pandas
  import argparse
  import collections
  import multiprocessing
  from concurrent.futures import ProcessPoolExecutor
  import logging
label_desc: Use image node_id 2 for calling a global function with example usage: load_wv_vocab(file) and returns: vocab