Function test_save_class_labels_from_data

catboost/pytest/test.py:7287–7329

(loss_function)

@pytest.mark.parametrize('loss_function', ['MultiClass', 'MultiClassOneVsAll', 'Logloss', 'RMSE'])
def test_save_class_labels_from_data(loss_function):
    labels = [10000000, 7, 0, 9999]

    model_path = yatest.common.test_output_path('model.bin')

    cd_path = yatest.common.test_output_path('cd.txt')
    np.savetxt(cd_path, [[0, 'Target']], fmt='%s', delimiter='\t')

    prng = np.random.RandomState(seed=0)

    train_path = yatest.common.test_output_path('train.txt')
    np.savetxt(train_path, generate_concatenated_random_labeled_dataset(100, 10, labels, prng=prng), fmt='%s', delimiter='\t')

    cmd = (
        '--loss-function', loss_function,
        '-f', train_path,
        '--column-description', cd_path,
        '-i', '10',
        '-T', '4',
        '-m', model_path,
        '--use-best-model', 'false',
    )

    if loss_function == 'Logloss':
        cmd += ('--target-border', '0.5')

    execute_catboost_fit('CPU', cmd)

    py_catboost = catboost.CatBoost()
    py_catboost.load_model(model_path)

    if loss_function in MULTICLASS_LOSSES:
        assert json.loads(py_catboost.get_metadata()['class_params'])['class_label_type'] == 'String'
        assert json.loads(py_catboost.get_metadata()['class_params'])['class_to_label'] == [0, 1, 2, 3]
        assert json.loads(py_catboost.get_metadata()['class_params'])['class_names'] == ['0.0', '7.0', '9999.0', '10000000.0']
        assert json.loads(py_catboost.get_metadata()['class_params'])['classes_count'] == 0
    elif loss_function == 'Logloss':
        assert json.loads(py_catboost.get_metadata()['class_params'])['class_label_type'] == 'Integer'
        assert json.loads(py_catboost.get_metadata()['class_params'])['class_to_label'] == [0, 1]
        assert json.loads(py_catboost.get_metadata()['class_params'])['class_names'] == []
        assert json.loads(py_catboost.get_metadata()['class_params'])['classes_count'] == 0
    else:
        assert 'class_params' not in py_catboost.get_metadata()


@pytest.mark.parametrize('prediction_type', ['Probability', 'RawFormulaVal', 'Class'])