code: def load_textcat_data(limit=0):
      
      # Partition off part of the train data for evaluation
      train_data, eval_data = thinc.extra.datasets.imdb()
      random.shuffle(train_data)
      train_data = train_data[-limit:]
      texts, labels = zip(*train_data)
      eval_texts, eval_labels = zip(*eval_data)
      cats = [{"POSITIVE": bool(y), "NEGATIVE": not bool(y)} for y in labels]
      eval_cats = [{"POSITIVE": bool(y), "NEGATIVE": not bool(y)} for y in eval_labels]
      return (texts, cats), (eval_texts, eval_cats)
docs: Load data from the IMDB dataset.