Fittransform first cut

  assert len(pred4e) == len(reloaded_pred4e)

  for (p4e, r4e) in zip(pred4e, reloaded_pred4e):

    assert p4e == r4e

def test_fittransform_regression_reload():

  """Test that MultitaskFitTransformRegressor can reload simple regression datasets."""

  n_samples = 10

  n_features = 3

  n_tasks = 1

  # Generate dummy dataset

  np.random.seed(123)

  tf.random.set_seed(123)

  ids = np.arange(n_samples)

  X = np.random.rand(n_samples, n_features, n_features)

  y = np.zeros((n_samples, n_tasks))

  w = np.ones((n_samples, n_tasks))

  dataset = dc.data.NumpyDataset(X, y, w, ids)

  fit_transformers = [dc.trans.CoulombFitTransformer(dataset)]

  regression_metric = dc.metrics.Metric(dc.metrics.mean_squared_error)

  model_dir = tempfile.mkdtemp()

  model = dc.models.MultitaskFitTransformRegressor(

      n_tasks, [n_features, n_features],

      dropouts=[0.01],

      weight_init_stddevs=[np.sqrt(6) / np.sqrt(1000)],

      batch_size=n_samples,

      fit_transformers=fit_transformers,

      n_evals=1,

      optimizer=Adam(learning_rate=0.003, beta1=0.9, beta2=0.999),

      model_dir=model_dir)

  # Fit trained model

  model.fit(dataset, nb_epoch=100)

  # Eval model on train

  scores = model.evaluate(dataset, [regression_metric])

  assert scores[regression_metric.name] < .1