input: Write a python function to analyze the sentiment of a given text using the NLTK library's SentimentIntensityAnalyzer.
  assert sentiment_analyzer('This is a good day!') == {'neg': 0.0, 'neu': 0.508, 'pos': 0.492, 'compound': 0.4404}
  assert sentiment_analyzer('I am extremely happy with the results.') == {'neg': 0.0, 'neu': 0.508, 'pos': 0.492, 'compound': 0.6997}
  assert sentiment_analyzer('This is the worst experience ever.') == {'neg': 0.536, 'neu': 0.464, 'pos': 0.0, 'compound': -0.6249}
output: def sentiment_analyzer(text):
      from nltk.sentiment import SentimentIntensityAnalyzer
      from nltk import download
      download('vader_lexicon')
      
      sia = SentimentIntensityAnalyzer()
      return sia.polarity_scores(text)