code: def test_inmemory_features_and_labels():
      smiles = ["C", "CC", "CCC", "CCCC"]
      labels = [1, 0, 1, 0]
      featurizer = dc.feat.CircularFingerprint(size=1024)
      loader = dc.data.InMemoryLoader(
          tasks=["task1"], featurizer=featurizer
      )
      dataset = loader.create_dataset(zip(smiles, labels), shard_size=2)
      assert len(dataset) == 4
      assert dataset.X.shape == (4, 1024)
      assert (dataset.y == np.array(labels)).all()
      assert dataset.get_number_shards() == 2
      assert (dataset.ids == np.arange(4)).all()
  
imports: import deepchem
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: test_inmemory_features_and_labels() without return types