code: def get_vector(self, tokens):
      vec = self.s.run(
          self.embedding,
          feed_dict={
              self.inputs["tokens"]: [tokens],
              self.inputs["sequence_len"]: [len(tokens)],
          },
      )
      return np.squeeze(vec, axis=0)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import os
  import sys
  from typing import List
  import numpy
  from gensim.models import FastText
  from nlp_architect.utils.text import Vocabulary
label_desc: Use image node_id 2 for calling the ELMoEmbedderTFHUB obj's underlying member method code with example usage: obj.get_vector(tokens) and returns: np