code: def test_has_annotations(
      self, dataset_mock, config, annotation_dp_type
  ):
      dataset, _ = dataset_mock.load(config)
  
      if not any(
          isinstance(dp, annotation_dp_type)
          for dp in extract_datapipes(dataset)
      ):
          raise AssertionError(
              f"The dataset doesn't contain a {annotation_dp_type.__name__}() datapipe."
          )
  
imports: import io
  import pickle
  from collections import deque
  from pathlib import Path
  import pytest
  import torch
  import torchvision.transforms.v2
  from builtin_dataset_mocks import DATASET_MOCKS, parametrize_dataset_mocks
  from torch.testing._comparison import not_close_error_metas, ObjectPair, TensorLikePair
  from torch.utils.data import DataLoader
  from torch.utils.data.graph_settings import get_all_graph_pipes
  from torchdata.dataloader2.graph.utils import traverse_dps
  from torchdata.datapipes.iter import ShardingFilter, Shuffler
  from torchdata.datapipes.utils import StreamWrapper
  from torchvision import tv_tensors
  from torchvision._utils import sequence_to_str
  from torchvision.prototype import datasets
  from torchvision.prototype.datasets.utils import EncodedImage
  from torchvision.prototype.datasets.utils._internal import INFINITE_BUFFER_SIZE
  from torchvision.prototype.tv_tensors import Label
  from torchvision.transforms.v2._utils import is_pure_tensor
label_desc: Use image node_id 13 for calling the TestCommon obj's underlying member method code with example usage: obj.test_has_annotations(dataset_mock, config, annotation_dp_type) without return types