input: Write a function to determine if a given sentence is an 'affirmative' sentence or a 'negative' sentence. If the sentence contains negation words, it is considered 'negative'; otherwise, it is 'affirmative'. If the sentence is empty, return "Affirmative". The function should use Natural Language Toolkit (NLTK) to tokenize the sentence and identify negation words.
  
  assert isAffirmativeorNegative("He always comes late but I dont mind.") == "Negative"
  assert isAffirmativeorNegative("She is always on time.") == "Affirmative"
  assert isAffirmativeorNegative("") == "Affirmative"
  assert isAffirmativeorNegative("I never go there.") == "Negative"
  assert isAffirmativeorNegative("There is no problem.") == "Negative"
output: def isAffirmativeorNegative(sentence):
      if not sentence:
          return "Affirmative"
      from nltk.tokenize import word_tokenize
      negation_words = {"not", "no", "never", "none", "nobody", "nothing", "neither", "nor", "nowhere", "hardly", "scarcely", "barely", "don't", "doesn't", "didn't", "can't", "couldn't", "won't", "wouldn't", "isn't", "aren't", "ain't"}
      tokens = set(word_tokenize(sentence.lower()))
      if tokens & negation_words:
          return "Negative"
      return "Affirmative"