input: def visualize_twitter_data(twitter_data: List[Dict[str, Union[str, int, float]]]) -> None:
      """ Visualize the Twitter data by plotting the number of tweets per author, 
      the number of likes per tweet, and the number of retweets per tweet using matplotlib.
      >>> visualize_twitter_data([{'author': 'user1', 'date': '2023-10-01', 'text': 'Hello', 'likes': 10, 'retweets': 5}, {'author': 'user2', 'date': '2023-10-02', 'text': 'Hi', 'likes': 20, 'retweets': 10}])
      (Plots a bar chart for Tweet Author Summary, Number of Likes Summary, and Number of Retweets Summary)
      """
output:     
      import matplotlib.pyplot as plt
      from collections import defaultdict
  
      # Count tweets per author
      author_count = defaultdict(int)
      for tweet in twitter_data:
          author_count[tweet['author']] += 1
  
      # Extract likes and retweets
      likes = [tweet['likes'] for tweet in twitter_data]
      retweets = [tweet['retweets'] for tweet in twitter_data]
  
      # Plotting
      fig, axs = plt.subplots(3, 1, figsize=(10, 15))
  
      # Plot tweets per author
      axs[0].bar(author_count.keys(), author_count.values(), color='blue')
      axs[0].set_title('Tweet Author Summary')
      axs[0].set_xlabel('Author')
      axs[0].set_ylabel('Number of Tweets')
  
      # Plot number of likes per tweet
      axs[1].hist(likes, bins=10, color='green')
      axs[1].set_title('Number of Likes Summary')
      axs[1].set_xlabel('Number of Likes')
      axs[1].set_ylabel('Frequency')
  
      # Plot number of retweets per tweet
      axs[2].hist(retweets, bins=10, color='red')
      axs[2].set_title('Number of Retweets Summary')
      axs[2].set_xlabel('Number of Retweets')
      axs[2].set_ylabel('Frequency')
  
      plt.tight_layout()
      plt.show()
  