input: Write a python function to find sentences containing nouns.
  assert find_nouns(["The cat sits on the mat.", "Running is fun.", "She sells seashells."]) == ["The cat sits on the mat.", "She sells seashells."]
  assert find_nouns(["I love programming.", "Jumping high!", "A beautiful garden."]) == ["I love programming.", "A beautiful garden."]
  assert find_nouns(["No nouns here.", "Absolutely none!", "Wait, a tree."]) == ["Wait, a tree."]
output: def find_nouns(sentences):
      import nltk
      nltk.download('punkt')
      nltk.download('averaged_perceptron_tagger')
      
      def contains_noun(sentence):
          words = nltk.word_tokenize(sentence)
          tagged = nltk.pos_tag(words)
          for word, tag in tagged:
              if tag.startswith('NN'):  # Check if the tag is a noun (NN, NNS, NNP, NNPS)
                  return True
          return False
  
      return [sentence for sentence in sentences if contains_noun(sentence)]