code: def test_sequence_rank(self):
      self.assertEqual(
          1,
          top_level_feature._get_sequence_rank(
              {
                  "a": features_lib.TensorInfo(
                      shape=(None, 3), dtype=np.int32, sequence_rank=1
                  ),
                  "b": features_lib.TensorInfo(
                      shape=(None,), dtype=np.int32, sequence_rank=1
                  ),
              }
          ),
      )
  
      with self.assertRaisesWithPredicateMatch(
          NotImplementedError, "mixing sequence and context"
      ):
          top_level_feature._get_sequence_rank(
              {
                  "a": features_lib.TensorInfo(
                      shape=(), dtype=np.int32
                  ),
                  "b": features_lib.TensorInfo(
                      shape=(None,), dtype=np.int32, sequence_rank=1
                  ),
              }
          )
  
file_path: datasets/tensorflow_datasets/core/features/top_level_feature_test.py
imports: import time
  import numpy
  from tensorflow_datasets import testing
  from tensorflow_datasets.core import features
  from tensorflow_datasets.core.features import top_level_feature
label_desc: Use image node_id 1 for calling the FeaturesManagerTest obj's underlying member method code with example usage: obj.test_sequence_rank() without return types