input: Write a python function to normalize text by removing punctuation and lemmatizing tokens.
  assert LemNormalize("Hello! How are you?") == ['hello', 'how', 'are', 'you']
  assert LemNormalize("Cats running quickly!") == ['cat', 'run', 'quickly']
  assert LemNormalize("The children are playing games.") == ['the', 'child', 'are', 'play', 'game']
output: def LemNormalize(text):
      import nltk
      from nltk.corpus import stopwords
      from nltk.tokenize import word_tokenize
      from nltk.stem import WordNetLemmatizer
      import string
  
      nltk.download('punkt')
      nltk.download('wordnet')
      nltk.download('stopwords')
  
      lemmatizer = WordNetLemmatizer()
      stop_words = set(stopwords.words('english'))
  
      # Tokenize the text
      tokens = word_tokenize(text)
  
      # Remove punctuation and lowercase the tokens
      tokens = [word.lower() for word in tokens if word.isalpha()]
  
      # Lemmatize tokens
      lemmatized_tokens = [lemmatizer.lemmatize(word) for word in tokens]
  
      return lemmatized_tokens