Added a test case

  assert noise < np.mean(std) < 1.0

def test_multitask_regressor_delaney_uncertainty():

  """Test computing uncertainty on a larger dataset."""

  tasks, datasets, transformers = dc.molnet.load_delaney('ECFP')

  train_dataset, valid_dataset, test_dataset = datasets

  model = dc.models.MultitaskRegressor(len(tasks), 1024, uncertainty=True)

  model.fit(train_dataset, nb_epoch=20)

  metric = dc.metrics.Metric(dc.metrics.pearsonr)

  scores = model.evaluate(test_dataset, [metric], transformers)

  assert scores['pearsonr'] > 0.5

@pytest.mark.slow

def test_DAG_singletask_regression_overfit():

  """Test DAG regressor multitask overfits tiny data."""