def METHOD_NAME():
    preds = np.array(
        [
            [[0.2, 0.1, 0.1, 0.1], [0.8, 0.9, 0.9, 0.9]],
            [[1.0, 1.0, 1.0, 1.0], [0.0, 0.0, 0.0, 0.0]],
            [[1.0, 1.0, 1.0, 0.2], [0.0, 0.0, 0.0, 0.8]],
            [[0.9, 0.8, 0.9, 1.0], [0.1, 0.2, 0.1, 0.0]],
        ]
    )
    clf = EEGClassifier(
        MockModule(preds),
        cropped=True,
        criterion=CroppedLoss,
        criterion__loss_function=nll_loss,
        optimizer=optim.Adam,
        batch_size=32,
        aggregate_predictions=False
    )
    clf.initialize()
    np.testing.assert_array_equal(preds.argmax(1), clf.predict(MockDataset()))
    np.testing.assert_array_equal(preds, clf.predict_proba(MockDataset()))