def METHOD_NAME(dtype, feature_type):
    # check that the input type is kept
    img = np.ones((5, 5), dtype=dtype)
    img_ii = integral_image(img)
    expected_dtype = img_ii.dtype
    # to avoid overflow, unsigned type are converted to signed
    if 'uint' in expected_dtype.name:
        expected_dtype = np.dtype(expected_dtype.name.replace('u', ''))
    haar_feature = haar_like_feature(img_ii, 0, 0, 5, 5,
                                     feature_type=feature_type)
    assert haar_feature.dtype == expected_dtype