code: def test_int(self):
      self.assertFeature(
          feature=feature_lib.Sequence({"int": np.int32}, length=3),
          shape={"int": (3,)},
          dtype={"int": np.int32},
          serialized_info={
              "int": feature_lib.TensorInfo(shape=(3,), dtype=np.int32),
          },
          tests=[
              # Python array
              testing.FeatureExpectationItem(
                  value={"int": [1, 2, 3]},
                  expected={"int": [1, 2, 3]},
                  expected_np={"int": [1, 2, 3]},
              ),
              # Numpy array
              testing.FeatureExpectationItem(
                  value={"int": np.ones(shape=(3,), dtype=np.int32)},
                  expected={"int": [1, 1, 1]},
                  expected_np={"int": [1, 1, 1]},
              ),
              # Array of dict
              testing.FeatureExpectationItem(
                  value=[
                      {"int": 1},
                      {"int": 10},
                      {"int": 100},
                  ],
                  expected={"int": [1, 10, 100]},
                  expected_np={"int": [1, 10, 100]},
              ),
              # Wrong sequence length
              testing.FeatureExpectationItem(
                  value={"int": np.ones(shape=(4,), dtype=np.int32)},
                  raise_cls=ValueError,
                  raise_cls_np=ValueError,
                  raise_msg="Input sequence length do not match",
              ),
          ],
          test_attributes=dict(_length=3),
      )
  
imports: import numpy
  import tensorflow
  from tensorflow_datasets import testing
  from tensorflow_datasets.core import features
label_desc: Use image node_id 1 for calling the SequenceDictFeatureTest obj's underlying member method code with example usage: obj.test_int() without return types