code: def test_tsf_predict_call_automodel_predict_fails(
      predict, fit, tmp_path
  ):
      auto_model = ak.TimeseriesForecaster(
          lookback=10, directory=tmp_path, seed=test_utils.SEED
      )
  
      auto_model.fit(x=test_utils.TRAIN_CSV_PATH, y="survived")
      # Predict data doesn't contain train time steps
      try:
          auto_model.predict(x=test_utils.TEST_CSV_PATH, y="survived")
      except ValueError as e:
          assert fit.is_called
          assert "The prediction data requires the original training data to make"
          " predictions on subsequent data points" in str(e)
  
imports: from unittest import mock
  import autokeras
  from autokeras import test_utils
label_desc: Use image node_id 3 for calling a global function with example usage: test_tsf_predict_call_automodel_predict_fails(predict, fit, tmp_path) without return types