code: def test_structured_data_classifier(tmp_path):
      num_data = NUM_INSTANCES * 2
      num_train = NUM_INSTANCES
      data = (
          pd.read_csv(test_utils.TRAIN_CSV_PATH)
          .to_numpy()
          .astype(str)[:num_data]
      )
      x_train, x_test = data[:num_train], data[num_train:]
      y = test_utils.generate_one_hot_labels(
          num_instances=num_data, num_classes=3
      )
      y_train, y_test = y[:num_train], y[num_train:]
      clf = ak.StructuredDataClassifier(
          directory=tmp_path, max_trials=1, seed=test_utils.SEED
      )
      clf.fit(
          x_train,
          y_train,
          epochs=2,
          validation_data=(x_train, y_train),
          batch_size=BATCH_SIZE,
      )
      clf.export_model()
      assert clf.predict(x_test).shape == (len(y_test), 3)
  
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 6 for calling a global function with example usage: test_structured_data_classifier(tmp_path) without return types