code: def test_2lvl_sequences(self):
      self.assertFeature(
          feature=feature_lib.Sequence(
              feature_lib.Sequence(
                  feature_lib.Tensor(shape=(2,), dtype=np.int32),
              ),
          ),
          shape=(None, None, 2),
          dtype=np.int32,
          test_tensor_spec=False,  # TODO(b/227584124): doesn't work
          tests=[
              testing.FeatureExpectationItem(
                  value=[
                      [[0, 1], [2, 3]],
                      [],
                      [[4, 5]],
                  ],
                  expected=testing.RaggedConstant(
                      [
                          [[0, 1], [2, 3]],
                          [],
                          [[4, 5]],
                      ],
                      inner_shape=(2,),
                  ),
                  expected_np=[
                      [[0, 1], [2, 3]],
                      [],
                      [[4, 5]],
                  ],
              ),
              # Empty
              testing.FeatureExpectationItem(
                  value=[],
                  expected=[],
                  expected_np=[],
              ),
              # List of empty lists
              testing.FeatureExpectationItem(
                  value=[[], [], []],
                  expected=[[], [], []],
                  expected_np=[[], [], []],
              ),
              # List of empty np.array
              testing.FeatureExpectationItem(
                  value=[
                      np.empty(shape=(0, 2), dtype=np.int32),
                      np.empty(shape=(0, 2), dtype=np.int32),
                  ],
                  expected=[
                      [],
                      [],
                  ],
                  expected_np=[
                      [],
                      [],
                  ],
              ),
              testing.FeatureExpectationItem(
                  value=[
                      np.empty(shape=(0, 2), dtype=np.int32),
                      np.empty(shape=(0, 2), dtype=np.int32),
                      np.ones(shape=(3, 2), dtype=np.int32),
                  ],
                  expected=[
                      [],
                      [],
                      [[1, 1], [1, 1], [1, 1]],
                  ],
                  expected_np=[
                      [],
                      [],
                      [[1, 1], [1, 1], [1, 1]],
                  ],
              ),
              # Wrong types should fails
              testing.FeatureExpectationItem(
                  value=[
                      np.ones(shape=(3, 2), dtype=np.float32),
                  ],
                  raise_cls=ValueError,
                  raise_cls_np=ValueError,
                  raise_msg="float32 do not match",
              ),
          ],
      )
  
imports: import numpy
  import tensorflow
  from tensorflow_datasets import testing
  from tensorflow_datasets.core import features
label_desc: Use image node_id 6 for calling the SequenceDictFeatureTest obj's underlying member method code with example usage: obj.test_2lvl_sequences() without return types