old_contents: try:
      import nltk
      from nltk.corpus import wordnet
  except ImportError:
      # No installation required if not using this function
      pass
  
  from nlpaug.model.word_dict import WordDictionary
  
  
  class WordNet(WordDictionary):
      def __init__(self, lang, is_synonym=True):
          super().__init__(cache=True)
  
          self.lang = lang
          self.is_synonym = is_synonym
          self.model = self.read()
  
          try:
              wordnet
          except NameError:
              raise ImportError('Missed nltk library. Install it via `pip install nltk`')
  
      @classmethod
      def read(cls):
          try:
              # Check whether wordnet package is downloaded
              wordnet.synsets('computer')
          except ImportError:
              nltk.download('wordnet')
  
          try:
              # Check whether POS package is downloaded
              nltk.pos_tag('computer')
          except ImportError:
              nltk.download('averaged_perceptron_tagger')
  
          return wordnet
  
      def predict(self, word, pos=None):
          results = []
          for synonym in self.model.synsets(word, pos=pos, lang=self.lang):
              for lemma in synonym.lemmas():
                  if self.is_synonym:
                      results.append(lemma.name())
                  else:
                      for antonym in lemma.antonyms():
                          results.append(antonym.name())
          return results
  
      @classmethod
      def pos_tag(cls, tokens):
          return nltk.pos_tag(tokens)
  
new_contents: try:
      import nltk
      from nltk.corpus import wordnet
  except ImportError:
      # No installation required if not using this function
      pass
  
  from nlpaug.model.word_dict import WordDictionary
  
  
  class WordNet(WordDictionary):
      def __init__(self, lang, is_synonym=True):
          super().__init__(cache=True)
  
          self.lang = lang
          self.is_synonym = is_synonym
  
          try:
              wordnet
          except NameError:
              raise ImportError('Missed nltk library. Install it via `pip install nltk`')
          try:
              # Check whether wordnet package is downloaded
              wordnet.synsets('computer')
              # Check whether POS package is downloaded
              nltk.pos_tag('computer')
          except ImportError:
              nltk.download('wordnet')
              nltk.download('averaged_perceptron_tagger')
  
          self.model = self.read()
  
      def read(self):
          return wordnet
  
      def predict(self, word, pos=None):
          results = []
          for synonym in self.model.synsets(word, pos=pos, lang=self.lang):
              for lemma in synonym.lemmas():
                  if self.is_synonym:
                      results.append(lemma.name())
                  else:
                      for antonym in lemma.antonyms():
                          results.append(antonym.name())
          return results
  
      @classmethod
      def pos_tag(cls, tokens):
          return nltk.pos_tag(tokens)
  
subject: fix loading ntlk and wordnet exception