code: def check_words_in_embeddings_voc(
      self, embedding, tuned=True, debug=False
  ):
      print("🌋 Checking if words are in embedding voc")
      if tuned:
          embed_voc = embedding.tun_idx
      else:
          embed_voc = embedding.stat_idx
      missing_words = []
      missing_words_sents = []
      missing_words_doc = []
      for doc in self.docs:
          # if debug: print("Checking doc", doc.name, doc.part)
          for sent in doc.utterances:
              # if debug: print(sent.text)
              for word in sent:
                  w = embedding.normalize_word(word)
                  # if debug: print(w)
                  if w not in embed_voc:
                      missing_words.append(w)
                      missing_words_sents.append(sent.text)
                      missing_words_doc.append(doc.name + doc.part)
                      if debug:
                          out_str = (
                              "No matching tokens in tuned voc for "
                              + w
                              + " in sentence "
                              + sent.text
                              + " in doc "
                              + doc.name
                              + doc.part
                          )
                          print(out_str)
      return missing_words, missing_words_sents, missing_words_doc
  
imports: import re
  import argparse
  import time
  import os
  import io
  import pickle
  import spacy
  import numpy
  from tqdm import tqdm
  from neuralcoref.train.compat import unicode_
  from neuralcoref.train.document import Mention, Document, Speaker, EmbeddingExtractor, MISSING_WORD, extract_mentions_spans
  from neuralcoref.train.utils import parallel_process
label_desc: Use image node_id 2 for calling the ConllCorpus obj's underlying member method code with example usage: obj.check_words_in_embeddings_voc(embedding, tuned, debug) and returns: missing_words,  missing_words_sents,  missing_words_doc