code: def test_merge():
      """Test that datasets can be merged."""
      current_dir = os.path.dirname(os.path.realpath(__file__))
  
      dataset_file = os.path.join(
          current_dir, "../../models/tests/assets/example.csv"
      )
  
      featurizer = dc.feat.CircularFingerprint(size=1024)
      tasks = ["log-solubility"]
      loader = dc.data.CSVLoader(
          tasks=tasks, feature_field="smiles", featurizer=featurizer
      )
      first_dataset = loader.create_dataset(dataset_file)
      first_dataset.reshard(10)
      second_dataset = loader.create_dataset(dataset_file)
  
      merged_dataset = dc.data.DiskDataset.merge(
          [first_dataset, second_dataset]
      )
  
      assert len(merged_dataset) == len(first_dataset) + len(
          second_dataset
      )
      assert merged_dataset.get_shard_size() == 10
  
      # Test merging of numpy datasets
      X1, y1 = np.random.rand(5, 3), np.random.randn(5, 1)
      first_dataset = dc.data.NumpyDataset(X1, y1)
      X2, y2 = np.random.rand(5, 3), np.random.randn(5, 1)
      second_dataset = dc.data.NumpyDataset(X2, y2)
      merged_dataset = dc.data.NumpyDataset.merge(
          [first_dataset, second_dataset]
      )
      assert len(merged_dataset) == len(first_dataset) + len(
          second_dataset
      )
  
imports: import os
  import deepchem
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: test_merge() without return types