def METHOD_NAME() -> None:
    from scipy.sparse import csr_matrix
    pd1 = pd.DataFrame(
        {
            "featureVectorType": [0, 1, 1, 0],
            "featureVectorSize": [3, None, None, 3],
            "featureVectorIndices": [
                np.array([0, 2], dtype=np.int32),
                None,
                None,
                np.array([1, 2], dtype=np.int32),
            ],
            "featureVectorValues": [
                np.array([3.0, 0.0], dtype=np.float64),
                np.array([13.0, 14.0, 0.0], dtype=np.float64),
                np.array([0.0, 24.0, 25.0], dtype=np.float64),
                np.array([0.0, 35.0], dtype=np.float64),
            ],
        }
    )
    sm = _read_csr_matrix_from_unwrapped_spark_vec(pd1)
    assert isinstance(sm, csr_matrix)
    np.testing.assert_array_equal(
        sm.data, [3.0, 0.0, 13.0, 14.0, 0.0, 0.0, 24.0, 25.0, 0.0, 35.0]
    )
    np.testing.assert_array_equal(sm.indptr, [0, 2, 5, 8, 10])
    np.testing.assert_array_equal(sm.indices, [0, 2, 0, 1, 2, 0, 1, 2, 1, 2])
    assert sm.shape == (4, 3)