input: Write a function to analyze the sentiment of a text using tokenization, stemming, and polarity scoring. The function should return a dictionary of polarity scores. If the input text is empty, the function should return an empty dictionary.
  assert sentiment_analyzer("I love this product!")=={'neg': 0.0, 'neu': 0.367, 'pos': 0.633, 'compound': 0.6249}
  assert sentiment_analyzer("This is the worst day ever.")=={'neg': 0.662, 'neu': 0.338, 'pos': 0.0, 'compound': -0.765}
  assert sentiment_analyzer("")=={}
output: def sentiment_analyzer(text):
      if not text:
          return {}
      from nltk.sentiment.vader import SentimentIntensityAnalyzer
      analyzer = SentimentIntensityAnalyzer()
      return analyzer.polarity_scores(text)