code: def movie_reviews_data():
      """Dataset of single sentence samples."""
      download_nltk_resources()
      sentences = [" ".join(x) for x in movie_reviews.sents()]
      random.seed(42)
  
      train_data = TextData(random.sample(sentences, k=10_000))
      test_data = TextData(random.sample(sentences, k=10_000))
      return train_data, test_data
  
imports: import random
  import typing
  import numpy
  import pytest
  from datasets import load_dataset
  from nltk import download
  from nltk.corpus import movie_reviews
  from deepchecks.nlp.datasets.classification import just_dance_comment_analysis, tweet_emotion
  from deepchecks.nlp.text_data import TextData
label_desc: Use image node_id 13 for calling a global function with example usage: movie_reviews_data() and returns: train_data,  test_data