2ef0e4b77a137e13d5cdfa635aef3d80959a47bd,deepchem/hyper/tests/test_gaussian_hyperparam_opt.py,TestGaussianHyperparamOpt,test_rf_example,#TestGaussianHyperparamOpt#,15

Before Change

    train_dataset = dc.data.NumpyDataset(
        X=np.random.rand(50, 5), y=np.random.rand(50, 1))
    valid_dataset = dc.data.NumpyDataset(
        X=np.random.rand(20, 5), y=np.random.rand(20, 1))
    optimizer = dc.hyper.GaussianProcessHyperparamOpt(rf_model_builder)
    params_dict = {"n_estimators": 10}
    transformers = [
        dc.trans.NormalizationTransformer(

After Change

        metric,
        max_iter=2)

    valid_score = best_model.evaluate(self.valid_dataset, [metric],
                                      transformers)
    assert valid_score["pearson_r2_score"] > 0

  def test_rf_with_logdir(self):
    Test that using a logdir can work correctly.

Instances