input: Write a function to determine whether a given sentence is an 'affirmative' sentence or a 'negative' sentence. If the sentence contains negation words, it should be classified as 'negative'; otherwise, it should be classified as 'affirmative'. The function should use the NLTK library to tokenize the sentence and identify negation words. If the given sentence is empty, it should return "Affirmative".
  
  assert isAffirmativeorNegative("He always comes late but I dont mind.") == "Negative"
  assert isAffirmativeorNegative("She is a brilliant student.") == "Affirmative"
  assert isAffirmativeorNegative("No one could find the missing key.") == "Negative"
  assert isAffirmativeorNegative("They will complete the project on time.") == "Affirmative"
  assert isAffirmativeorNegative("") == "Affirmative"
output: def isAffirmativeorNegative(sentence):
      if not sentence:
          return "Affirmative"
      negation_words = {"no", "not", "never", "none", "nobody", "nothing", "neither", "nor"}
      tokens = set(word.lower() for word in nltk.word_tokenize(sentence))
      for word in tokens:
          if word in negation_words:
              return "Negative"
      return "Affirmative"