code: def load_embedding(path):
      """
      return embedding for a specific file by given file path.
      """
      EMBEDDING_DIM = 300
      embedding_dict = {}
      with open(path, "r", encoding="utf-8") as file:
          pairs = [
              line.strip("\r\n").split() for line in file.readlines()
          ]
          for pair in pairs:
              if len(pair) == EMBEDDING_DIM + 1:
                  embedding_dict[pair[0]] = [float(x) for x in pair[1:]]
      logger.debug("embedding_dict size: %d", len(embedding_dict))
      return embedding_dict
  
imports: import os
  import logging
label_desc: Use image node_id 3 for calling a global function with example usage: load_embedding(path) and returns: embedding_dict