code: def get_avrg_feature_vector(self, tokens_str):
      embed = np.zeros(300, dtype=np.float64)
      mention_size = 0
      for token in tokens_str.split():
          if token in self.word_to_ix:
              token_embed = self.word_embeddings[self.word_to_ix[token]]
              embed = np.add(embed, token_embed)
              mention_size += 1
  
      if mention_size == 0:
          mention_size = 1
  
      return np.true_divide(embed, mention_size)
  
file_path: nlp-architect/nlp_architect/data/cdc_resources/embedding/embed_glove.py
imports: import logging
  import pickle
  import numpy
  from nlp_architect.common.cdc.mention_data import MentionDataLight
label_desc: Use image node_id 3 for calling the GloveEmbeddingOffline obj's underlying member method code with example usage: obj.get_avrg_feature_vector(tokens_str) and returns: np