input: Write a function to extract the top 10 most frequent words from a given text using natural language processing in Python. If the text is empty, return an empty list. Split the text into individual words using whitespace as the delimiter and use the Counter object from the collections module to count word frequencies.
  assert extract_top_words("Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.")==[('dolor', 1), ('Lorem', 1), ('ipsum', 1), ('amet', 1), ('consectetur', 1), ('adipiscing', 1), ('elit,', 1), ('sed', 1), ('do', 1), ('eiusmod', 1)]
  assert extract_top_words("apple apple banana cherry banana cherry banana cherry")==[('banana', 3), ('cherry', 3), ('apple', 2)]
  assert extract_top_words("")==[]
output: def extract_top_words(text):
      if not text:
          return []
      from collections import Counter
      words = text.split()
      word_counts = Counter(words)
      return word_counts.most_common(10)