code: def lemmatize(text, lowercase=True, remove_stopwords=True):
      
      doc = nlp(text)
      if lowercase and remove_stopwords:
          lemmas = [t.lemma_.lower() for t in doc if not (t.is_stop or t.orth_.lower() in STOPWORDS)]
      elif lowercase:
          lemmas = [t.lemma_.lower() for t in doc]
      elif remove_stopwords:
          lemmas = [t.lemma_ for t in doc if not (t.is_stop or t.orth_.lower() in STOPWORDS)]
      else:
          lemmas = [t.lemma_ for t in doc]
  
      return lemmas
docs: Return the lemmas of the tokens in a text.