code: def _get_train_test_indexes() -> t.Tuple[np.array, np.array]:
      """Get the indexes of the train and test sets."""
      if (ASSETS_DIR / "tweet_emotion_data.csv").exists():
          dataset = pd.read_csv(
              ASSETS_DIR / "tweet_emotion_data.csv",
              index_col=0,
              usecols=["Unnamed: 0", "train_test_split"],
          )
      else:
          dataset = pd.read_csv(
              _FULL_DATA_URL,
              index_col=0,
              usecols=["Unnamed: 0", "train_test_split"],
          )
  
      train_indexes = dataset[
          dataset["train_test_split"] == "Train"
      ].index
      test_indexes = dataset[
          dataset["train_test_split"] == "Test"
      ].index
      return train_indexes, test_indexes
  
file_path: deepchecks/deepchecks/nlp/datasets/classification/tweet_emotion.py
imports: import pathlib
  import typing
  import warnings
  import numpy
  import pandas
  from deepchecks.nlp import TextData
  from deepchecks.utils.builtin_datasets_utils import read_and_save_data
label_desc: Use image node_id 6 for calling a global function with example usage: _get_train_test_indexes() and returns: train_indexes,  test_indexes