code: def test_timeseries_forecaster(tmp_path):
      lookback = 2
      predict_from = 1
      predict_until = 10
      train_x = test_utils.generate_data_with_categorical(
          num_instances=100
      )
      train_y = test_utils.generate_data(num_instances=80, shape=(1,))
      clf = ak.TimeseriesForecaster(
          lookback=lookback,
          directory=tmp_path,
          predict_from=predict_from,
          predict_until=predict_until,
          max_trials=2,
          seed=test_utils.SEED,
      )
      clf.fit(
          train_x, train_y, epochs=1, validation_data=(train_x, train_y)
      )
      keras_model = clf.export_model()
      clf.evaluate(train_x, train_y)
      assert clf.predict(train_x).shape == (
          predict_until - predict_from + 1,
          1,
      )
      assert clf.fit_and_predict(
          train_x, train_y, epochs=1, validation_split=0.2
      ).shape == (predict_until - predict_from + 1, 1)
      assert isinstance(keras_model, keras.Model)
  
file_path: autokeras/autokeras/integration_tests/task_api_test.py
imports: import numpy
  import pandas
  import tensorflow
  from tensorflow import keras
  import autokeras
  from autokeras import test_utils
label_desc: Use image node_id 7 for calling a global function with example usage: test_timeseries_forecaster(tmp_path) without return types