input: from typing import List
  
  def sentiment_analyzer(text: str):
      """Analyze the sentiment of the given text using tokenization, stemming, and
      the SentimentIntensityAnalyzer.
      
      >>> sentiment_analyzer("I love this awesome product!")
      {'neg': 0.0, 'neu': 0.319, 'pos': 0.681, 'compound': 0.6369}
      >>> sentiment_analyzer("I absolutely hate this terrible product.")
      {'neg': 0.625, 'neu': 0.375, 'pos': 0.0, 'compound': -0.7579}
      """
output:     from nltk.tokenize import word_tokenize
      from nltk.stem import PorterStemmer
      from nltk.sentiment import SentimentIntensityAnalyzer
  
      # Tokenize the text
      tokens = word_tokenize(text)
  
      # Stem the tokens
      stemmer = PorterStemmer()
      stemmed_tokens = [stemmer.stem(token) for token in tokens]
  
      # Analyze sentiment
      sia = SentimentIntensityAnalyzer()
      sentiment_scores = sia.polarity_scores(' '.join(stemmed_tokens))
  
      return sentiment_scores