code: def glove_dump():
      filter_stop_words = False
      glove_file = args.glove
      out_file = args.output
      mention_files = [args.mentions]
      vocab = load_mentions_vocab_from_files(
          mention_files, filter_stop_words
      )
      word_to_ix, embeddings = load_glove_for_vocab(glove_file, vocab)
  
      logger.info("Words in vocabulary %d", len(vocab))
      logger.info(
          "Found %d words from vocabulary", len(word_to_ix.keys())
      )
      with open(out_file, "wb") as f:
          pickle.dump([word_to_ix, embeddings], f)
      logger.info("Saving dump to file-%s", out_file)
  
file_path: nlp-architect/nlp_architect/data/cdc_resources/gen_scripts/create_word_embed_glove_dump.py
imports: import argparse
  import logging
  import pickle
  import numpy
  from nlp_architect.models.cross_doc_coref.system.cdc_utils import load_mentions_vocab_from_files
  from nlp_architect.utils import io
label_desc: Use image node_id 2 for calling a global function with example usage: glove_dump() without return types