code: def test_random_test_train_valid_test_split():
      """Test of singletask RF ECFP regression API."""
      current_dir = os.path.dirname(os.path.abspath(__file__))
      tasks = ["log-solubility"]
      input_file = os.path.join(
          current_dir, "../../models/tests/assets/example.csv"
      )
      featurizer = dc.feat.CircularFingerprint(size=1024)
  
      input_file = os.path.join(current_dir, input_file)
      loader = dc.data.CSVLoader(
          tasks=tasks, feature_field="smiles", featurizer=featurizer
      )
  
      dataset = loader.create_dataset(input_file)
  
      # Splits featurized samples into train/test
      splitter = dc.splits.RandomSplitter()
      (
          train_dataset,
          valid_dataset,
          test_dataset,
      ) = splitter.train_valid_test_split(dataset)
      assert len(train_dataset) == 8
      assert len(valid_dataset) == 1
      assert len(test_dataset) == 1
  
file_path: deepchem/deepchem/data/tests/test_data_loader.py
imports: import os
  import tempfile
  import shutil
  import deepchem
label_desc: Use image node_id 4 for calling a global function with example usage: test_random_test_train_valid_test_split() without return types