code: def get_mention_vec_from_sent(sent_vec, indexs):
      if len(indexs) > 1:
          elmo_ret_vec = np.mean(
              sent_vec[indexs[0] : indexs[-1] + 1], axis=0
          )
      else:
          elmo_ret_vec = sent_vec[indexs[0]]
  
      return elmo_ret_vec
  
file_path: nlp-architect/nlp_architect/data/cdc_resources/embedding/embed_elmo.py
imports: import logging
  import pickle
  from typing import List
  import numpy
  from nlp_architect.common.cdc.mention_data import MentionDataLight
  from nlp_architect.utils.embedding import ELMoEmbedderTFHUB
label_desc: Use image node_id 6 for calling the ElmoEmbedding obj's underlying member method code with example usage: obj.get_mention_vec_from_sent(sent_vec, indexs) and returns: elmo_ret_vec