code: def test_given_linear_categorical_data_when_using_auto_gluon_classifier_linear_then_provides_good_fit():
      X, y = _generate_linear_classification_data(
          num_samples=1000, noise_std=0.2
      )
  
      x_train, x_test, y_train, y_test = train_test_split(
          X, y, test_size=0.5
      )
  
      y_test = shape_into_2d(y_test)
      with tempfile.TemporaryDirectory() as temp_dir:
          model = AutoGluonClassifier(
              path=temp_dir, time_limit=60, hyperparameters={"LR": {}}
          )
          model.fit(x_train, y_train)
  
      assert np.sum(
          model.predict(x_test).squeeze() == y_test.squeeze()
      ) / x_test.shape[0] == approx(1, abs=0.1)
  
file_path: dowhy/tests/gcm/ml/test_autogluon.py
imports: import tempfile
  import numpy
  from flaky import flaky
  from pytest import approx, importorskip, mark
  from sklearn.model_selection import train_test_split
  from dowhy.gcm.causal_mechanisms import AdditiveNoiseModel, ClassifierFCM
  from dowhy.gcm.ml.autogluon import AutoGluonClassifier, AutoGluonRegressor
  from dowhy.gcm.util.general import shape_into_2d
label_desc: Use image node_id 1 for calling a global function with example usage: test_given_linear_categorical_data_when_using_auto_gluon_classifier_linear_then_provides_good_fit() without return types