code: def test_get_dataset():
      ## semisupervised
      # NCI1
      root = "./dataset/TUDataset"
      dataset, dataset_pretrain = get_dataset(
          name="NCI1",
          task="semisupervised",
          feat_str="deg+odeg100",
          root=root,
      )
      assert len(dataset) == 4110
      assert len(dataset_pretrain) == 4110
      assert dataset.num_features == 139
      assert dataset_pretrain.num_features == 139
  
      assert dataset[0].x.size() == (21, 139)
      assert dataset_pretrain[0].x.size() == (21, 139)
      assert dataset[0].y.size() == (1,)
      assert dataset_pretrain[0].y.size() == (1,)
      assert dataset[0].edge_index.size() == (2, 42)
      assert dataset_pretrain[0].edge_index.size() == (2, 42)
      shutil.rmtree(root)
  
      #     # PROTEINS
      #     root = './dataset/TUDataset'
      #     dataset, dataset_pretrain = get_dataset(name='PROTEINS', task='semisupervised', feat_str='deg+odeg100', root=root)
      #     assert len(dataset) == 1113
      #     assert len(dataset_pretrain) == 1113
      #     assert dataset.num_features == 106
      #     assert dataset_pretrain.num_features == 106
  
      #     assert dataset[0].x.size() == (42, 106)
      #     assert dataset_pretrain[0].x.size() == (42, 106)
      #     assert dataset[0].y.size() == (1,)
      #     assert dataset_pretrain[0].y.size() == (1,)
      #     assert dataset[0].edge_index.size() == (2, 162)
      #     assert dataset_pretrain[0].edge_index.size() == (2,162)
      #     shutil.rmtree(root)
  
      #     # DD
      #     root = './dataset/TUDataset'
      #     dataset, dataset_pretrain = get_dataset(name='DD', task='semisupervised', feat_str='deg+odeg100', root=root)
      #     assert len(dataset) == 1178
      #     assert len(dataset_pretrain) == 1178
      #     assert dataset.num_features == 101
      #     assert dataset_pretrain.num_features == 101
  
      #     assert dataset[0].x.size() == (327, 101)
      #     assert dataset_pretrain[0].x.size() == (327, 101)
      #     assert dataset[0].y.size() == (1,)
      #     assert dataset_pretrain[0].y.size() == (1,)
      #     assert dataset[0].edge_index.size() == (2, 1798)
      #     assert dataset_pretrain[0].edge_index.size() == (2, 1798)
      #     shutil.rmtree(root)
  
      #     # COLLAB
      #     root = './dataset/TUDataset'
      #     dataset, dataset_pretrain = get_dataset(name='COLLAB', task='semisupervised', feat_str='deg+odeg100', root=root)
      #     assert len(dataset) == 5000
      #     assert len(dataset_pretrain) == 5000
      #     assert dataset.num_features == 103
      #     assert dataset_pretrain.num_features == 103
  
      #     assert dataset[0].x.size() == (45, 103)
      #     assert dataset_pretrain[0].x.size()  == (45, 103)
      #     assert dataset[0].y.size() == (1,)
      #     assert dataset_pretrain[0].y.size() == (1,)
      #     assert dataset[0].edge_index.size() == (2, 1980)
      #     assert dataset_pretrain[0].edge_index.size() == (2, 1980)
      #     shutil.rmtree(root)
  
      # REDDIT-BINARY
      # root = './dataset/TUDataset'
      # dataset, dataset_pretrain = get_dataset(name='REDDIT-BINARY', task='semisupervised', feat_str='deg+odeg100', root=root)
      # assert len(dataset) == 2000
      # assert len(dataset_pretrain) == 2000
      # assert dataset.num_features == 13
      # assert dataset_pretrain.num_features == 13
  
      # assert dataset[0].x.size() == (218, 13)
      # assert dataset_pretrain[0].x.size() == (218, 13)
      # assert dataset[0].y.size() == (1,)
      # assert dataset_pretrain[0].y.size() == (1,)
      # assert dataset[0].edge_index.size() == (2, 480)
      # assert dataset_pretrain[0].edge_index.size() == (2, 480)
      # shutil.rmtree(root)
  
      #     # REDDIT-MULTI-5K
      #     root = './dataset/TUDataset'
      #     dataset, dataset_pretrain = get_dataset(name='REDDIT-MULTI-5K', task='semisupervised', feat_str='deg+odeg100', root=root)
      #     assert len(dataset) == 4999
      #     assert len(dataset_pretrain) == 4999
      #     assert dataset.num_features == 13
      #     assert dataset_pretrain.num_features == 13
  
      #     assert dataset[0].x.size() == (1593, 13)
      #     assert dataset_pretrain[0].x.size() == (1593, 13)
      #     assert dataset[0].y.size() == (1,)
      #     assert dataset_pretrain[0].y.size() == (1,)
      #     assert dataset[0].edge_index.size() == (2, 3776)
      #     assert dataset_pretrain[0].edge_index.size() == (2, 3776)
      #     shutil.rmtree(root)
  
      ## unsupervised
      # NCI1
      root = "./dataset/TUDataset"
      dataset = get_dataset(
          name="NCI1",
          task="unsupervised",
          feat_str="deg+odeg100",
          root=root,
      )
      assert len(dataset) == 4110
      assert dataset.num_features == 43
  
      assert dataset[0].x.size() == (21, 43)
      assert dataset[0].y.size() == (1,)
      assert dataset[0].edge_index.size() == (2, 62)
      shutil.rmtree(root)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_get_dataset() without return types