code: def get_head_feature_vector(self, mention: MentionDataLight):
      if (
          mention.mention_context is not None
          and mention.mention_context
      ):
          sentence = " ".join(mention.mention_context)
          return self.apply_get_from_cache(
              sentence, True, mention.tokens_number
          )
  
      sentence = mention.tokens_str
      return self.apply_get_from_cache(sentence, False, [])
  
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 2 for calling the ElmoEmbedding obj's underlying member method code with example usage: obj.get_head_feature_vector(mention) and returns: self, self