input: Write a python function to generate feature vectors from a given text using CountVectorizer from sklearn.
  assert generate_feature_vectors(["This is a sample text about natural language processing."]).tolist() == [[1, 1, 1, 1, 1, 1, 1]]
  assert generate_feature_vectors(["Machine learning is fun and exciting."]).tolist() == [[1, 1, 1, 1, 1]]
  assert generate_feature_vectors(["Python is great for data science."]).tolist() == [[1, 1, 1, 1, 1]]
output: from sklearn.feature_extraction.text import CountVectorizer
  
  def generate_feature_vectors(texts):
      vectorizer = CountVectorizer()
      vectors = vectorizer.fit_transform(texts)
      return vectors