code: def test_singletask_sklearn_rf_ECFP_regression_API():
      """Test of singletask RF ECFP regression API."""
      X = np.random.rand(100, 5)
      y = np.random.rand(
          100,
      )
      dataset = dc.data.NumpyDataset(X, y)
  
      splitter = dc.splits.RandomSplitter()
      train_dataset, test_dataset = splitter.train_test_split(dataset)
  
      transformer = dc.trans.NormalizationTransformer(
          transform_y=True, dataset=train_dataset
      )
      train_dataset = transformer.transform(train_dataset)
      test_dataset = transformer.transform(test_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
      _ = model.evaluate(
          train_dataset, regression_metrics, [transformer]
      )
      _ = model.evaluate(
          test_dataset, regression_metrics, [transformer]
      )
  
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 1 for calling a global function with example usage: test_singletask_sklearn_rf_ECFP_regression_API() without return types