input: def classify_sentiment_of_movie_review(review: str) -> str:
      """ Classify the sentiment of a given movie review using VADER sentiment analysis.
      >>> classify_sentiment_of_movie_review('The movie was terrible. It felt like it would never end!')
      The sentiment of the sentence is negative!
      """
  
      from nltk.sentiment import vader
      
      sid = vader.SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(review)
  
      if scores['neg'] > scores['pos']:
          return 'The sentiment of the sentence is negative!'
      else:
          return 'The sentiment of the sentence is positive!'
output:     from nltk.sentiment import vader
      
      sid = vader.SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(review)
  
      if scores['neg'] > scores['pos']:
          return 'The sentiment of the sentence is negative!'
      else:
          return 'The sentiment of the sentence is positive!'