input: from typing import Dict, Union
  
  def sentiment_analyzer(text: str) -> Dict[str, Union[float, int]]:
      """Analyze the sentiment of a given text and return the sentiment polarity score.
      The score is a dictionary containing 'neg', 'neu', 'pos', and 'compound' keys, 
      representing the negative, neutral, positive, and compound sentiment scores respectively.
      >>> sentiment_analyzer("I love this product!")
      {'neg': 0.0, 'neu': 0.254, 'pos': 0.746, 'compound': 0.8316}
      >>> sentiment_analyzer("This is a neutral statement.")
      {'neg': 0.0, 'neu': 0.657, 'pos': 0.343, 'compound': 0.3612}
      >>> sentiment_analyzer("I hate this product.")
      {'neg': 0.581, 'neu': 0.419, 'pos': 0.0, 'compound': -0.5719}
      """
output:     
      from nltk.sentiment import SentimentIntensityAnalyzer
  
      sia = SentimentIntensityAnalyzer()
      sentiment = sia.polarity_scores(text)
      return sentiment
  