0d0bf039265afd094eebfd4cd5bb1bc8438a5ec1,deepchem/models/tests/test_api.py,TestAPI,test_singletask_sklearn_rf_user_specified_regression_API,#TestAPI#,100

Before Change

      for transformer in transformers:
        dataset = transformer.transform(dataset)

    regression_metrics = [Metric(metrics.r2_score),
                          Metric(metrics.mean_squared_error),
                          Metric(metrics.mean_absolute_error)]

    sklearn_model = RandomForestRegressor()
    model = SklearnModel(sklearn_model, self.model_dir)

    // Fit trained model
    model.fit(train_dataset)
    model.save()

    // Eval model on train
    evaluator = Evaluator(model, train_dataset, transformers, verbosity=True)
    _ = evaluator.compute_model_performance(regression_metrics)

    // Eval model on test
    evaluator = Evaluator(model, test_dataset, transformers, verbosity=True)
    _ = evaluator.compute_model_performance(regression_metrics)


  def test_singletask_sklearn_rf_RDKIT_descriptor_regression_API(self):
    Test of singletask RF RDKIT-descriptor regression API.

After Change

    splitter = dc.splits.SpecifiedSplitter(input_file, "split")
    train_dataset, test_dataset = splitter.train_test_split(dataset)

    transformers = [dc.transformers.NormalizationTransformer(
        transform_y=True, dataset=train_dataset)]
    for dataset in [train_dataset, test_dataset]:
      for transformer in transformers:
        dataset = transformer.transform(dataset)

Instances