code: def test_singletask_sklearn_rf_RDKIT_descriptor_regression_API():
      """Test of singletask RF RDKIT-descriptor regression API."""
      featurizer = dc.feat.RDKitDescriptors()
      tasks = ["log-solubility"]
  
      current_dir = os.path.dirname(os.path.abspath(__file__))
      input_file = os.path.join(current_dir, "assets/example.csv")
      loader = dc.data.CSVLoader(
          tasks=tasks, feature_field="smiles", featurizer=featurizer
      )
      dataset = loader.create_dataset(input_file)
  
      splitter = dc.splits.ScaffoldSplitter()
      train_dataset, test_dataset = splitter.train_test_split(dataset)
  
      transformers = [
          dc.trans.NormalizationTransformer(
              transform_X=True, dataset=train_dataset
          ),
          dc.trans.ClippingTransformer(
              transform_X=True, dataset=train_dataset
          ),
          dc.trans.NormalizationTransformer(
              transform_y=True, dataset=train_dataset
          ),
      ]
      for dataset in [train_dataset, test_dataset]:
          for transformer in transformers:
              dataset = transformer.transform(dataset)
  
      regression_metrics = [
          dc.metrics.Metric(dc.metrics.r2_score),
          dc.metrics.Metric(dc.metrics.mean_squared_error),
          dc.metrics.Metric(dc.metrics.mean_absolute_error),
      ]
  
      sklearn_model = RandomForestRegressor()
      model = dc.models.SklearnModel(sklearn_model)
  
      # Fit trained model
      model.fit(train_dataset)
      model.save()
  
      # Eval model on train/test
      _ = model.evaluate(
          train_dataset, regression_metrics, transformers
      )
      _ = model.evaluate(test_dataset, regression_metrics, transformers)
  
file_path: deepchem/deepchem/models/tests/test_api.py
imports: import os
  import pytest
  import deepchem
  import numpy
  from sklearn.ensemble import RandomForestRegressor
label_desc: Use image node_id 3 for calling a global function with example usage: test_singletask_sklearn_rf_RDKIT_descriptor_regression_API() without return types