input: Write a function to classify the sentiment of movie reviews using Natural Language Processing. The function should use VADER sentiment analysis and print the sentiment as either "positive" or "negative" based on the given sentence.
  import nltk
  from nltk.sentiment import vader
  
  def classify_sentiment(sentence):
      sid = vader.SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(sentence)
      if scores['neg'] > scores['pos']:
          print('The sentiment of the sentence is negative!')
      else:
          print('The sentiment of the sentence is positive!')
  
  assert classify_sentiment('The movie was terrible. It felt like it would never end!')=='The sentiment of the sentence is negative!'
  assert classify_sentiment('The movie was amazing. I loved every second of it!')=='The sentiment of the sentence is positive!'
  assert classify_sentiment('The movie was okay.')=='The sentiment of the sentence is positive!'
  assert classify_sentiment('This movie was absolutely horrendous.')=='The sentiment of the sentence is negative!'
  assert classify_sentiment('')=='The sentiment of the sentence is positive!'
output: def classify_sentiment(sentence):
      sid = vader.SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(sentence)
      if scores['neg'] > scores['pos']:
          print('The sentiment of the sentence is negative!')
      else:
          print('The sentiment of the sentence is positive!')