code: def character_vector_generator(data, start=0):
      """
      Character word vector generator util.
      Transforms a list of sentences into numpy int vectors of the characters
      of the words of the sentence, and returns the constructed vocabulary
  
      Arguments:
          data (list): list of list of strings
          start (int, optional): vocabulary index start integer
  
      Returns:
          np.array: a 2D numpy array
          Vocabulary: constructed vocabulary
      """
      vocab = Vocabulary(start)
      data_vec = []
      for sentence in data:
          sentence_vec = []
          for w in sentence:
              word_vec = []
              for char in w:
                  cid = vocab.add(char)
                  word_vec.append(cid)
              sentence_vec.append(word_vec)
          data_vec.append(sentence_vec)
      return data_vec, vocab
  
imports: import re
  import string
  import sys
  from os import path
  from typing import List, Tuple
  import spacy
  from nltk import WordNetLemmatizer
  from nltk.stem.snowball import EnglishStemmer
  from spacy.cli.download import download
  from spacy.lang.en import LEMMA_EXC, LEMMA_INDEX, LEMMA_RULES
  from spacy.lemmatizer import Lemmatizer
  from nlp_architect.utils.generic import license_prompt
  from joblib import Parallel, delayed
  from functools import partial
  from spacy.util import minibatch
  from nlp_architect.common.core_nlp_doc import CoreNLPDoc
  from pathlib import Path
label_desc: Use image node_id 8 for calling a global function with example usage: character_vector_generator(data, start) and returns: data_vec,  vocab