code: def load_glove_for_vocab(glove_filename):
      vocab = []
      embd = []
      with open(glove_filename) as glove_file:
          for line in glove_file:
              row = line.strip().split(" ")
              word = row[0]
              vocab.append(word)
              embd.append(row[1:])
  
      embeddings = np.asarray(embd, dtype=float)
      word_to_ix = {word: i for i, word in enumerate(vocab)}
      return word_to_ix, embeddings
  
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 2 for calling the GloveEmbedding obj's underlying member method code with example usage: obj.load_glove_for_vocab(glove_filename) and returns: word_to_ix,  embeddings