code: def load_embedding_txt(path):
      file_open = gzip.open if path.endswith(".gz") else open
      words = []
      vals = []
      with file_open(path, encoding="utf-8") as fin:
          fin.readline()
          for line in fin:
              line = line.rstrip()
              if line:
                  parts = line.split(" ")
                  words.append(parts[0])
                  vals += [float(x) for x in parts[1:]]
      return words, np.asarray(vals).reshape(len(words), -1)
  
imports: import gzip
  import os
  import sys
  import re
  import random
  import numpy
  import torch
label_desc: Use image node_id 15 for calling a global function with example usage: load_embedding_txt(path) and returns: words,  np