input: Write a python function to normalize a given text by removing punctuations and lemmatizing tokens.
  assert LemNormalize("The quick brown fox jumps over the lazy dog.") == ['the', 'quick', 'brown', 'fox', 'jump', 'over', 'the', 'lazy', 'dog']
  assert LemNormalize("Hello, World!") == ['hello', 'world']
  assert LemNormalize("Pythons are non-venomous snakes.") == ['python', 'are', 'nonvenomous', 'snake']
output: def LemNormalize(text):
      import nltk
      from nltk.corpus import wordnet
      from nltk.stem import WordNetLemmatizer
      import string
      
      # Download resources if not already present
      nltk.download('punkt')
      nltk.download('wordnet')
      
      # Initialize lemmatizer
      lemmatizer = WordNetLemmatizer()
      
      # Tokenize the text
      tokens = nltk.word_tokenize(text)
      
      # Remove punctuations and lowercase the tokens
      tokens = [word.lower() for word in tokens if word.isalnum()]
      
      # Lemmatize tokens
      normalized_tokens = [lemmatizer.lemmatize(word) for word in tokens]
      
      return normalized_tokens